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In a comparative oncology study with progression-free or overall survival as the endpoint, the primary or key secondary analysis is routinely stratified by patients' baseline characteristics when evaluating the treatment difference. The validity of a conventional strategy such as a stratified HR analysis depends on stringent model assumptions that are unlikely to be met in practice, especially in immunotherapy studies. Thus, the resulting summary is generally neither valid nor interpretable. This article discusses issues with conventional stratified analyses and presents alternatives using data from KEYNOTE-189, a recent immunotherapy trial for treating patients with metastatic, non-squamous, non-small-cell lung cancer., Competing Interests: Competing interests: There are no competing interests., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The immune microenvironment influences tumour evolution and can be both prognostic and predict response to immunotherapy 1,2 . However, measurements of tumour infiltrating lymphocytes (TILs) are limited by a shortage of appropriate data. Whole-exome sequencing (WES) of DNA is frequently performed to calculate tumour mutational burden and identify actionable mutations. Here we develop T cell exome TREC tool (T cell ExTRECT), a method for estimation of T cell fraction from WES samples using a signal from T cell receptor excision circle (TREC) loss during V(D)J recombination of the T cell receptor-α gene (TCRA (also known as TRA)). TCRA T cell fraction correlates with orthogonal TIL estimates and is agnostic to sample type. Blood TCRA T cell fraction is higher in females than in males and correlates with both tumour immune infiltrate and presence of bacterial sequencing reads. Tumour TCRA T cell fraction is prognostic in lung adenocarcinoma. Using a meta-analysis of tumours treated with immunotherapy, we show that tumour TCRA T cell fraction predicts immunotherapy response, providing value beyond measuring tumour mutational burden. Applying T cell ExTRECT to a multi-sample pan-cancer cohort reveals a high diversity of the degree of immune infiltration within tumours. Subclonal loss of 12q24.31-32, encompassing SPPL3, is associated with reduced TCRA T cell fraction. T cell ExTRECT provides a cost-effective technique to characterize immune infiltrate alongside somatic changes., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Immune checkpoint blockade (ICB) of PD-1 and CTLA-4 to treat metastatic melanoma (MM) has variable therapeutic benefit. To explore this in peripheral samples, we characterized CD8 + T cell gene expression across a cohort of patients with MM receiving anti-PD-1 alone (sICB) or in combination with anti-CTLA-4 (cICB). Whereas CD8 + transcriptional responses to sICB and cICB involve a shared gene set, the magnitude of cICB response is over fourfold greater, with preferential induction of mitosis- and interferon-related genes. Early samples from patients with durable clinical benefit demonstrated overexpression of T cell receptor-encoding genes. By mapping T cell receptor clonality, we find that responding patients have more large clones (those occupying >0.5% of repertoire) post-treatment than non-responding patients or controls, and this correlates with effector memory T cell percentage. Single-cell RNA-sequencing of eight post-treatment samples demonstrates that large clones overexpress genes implicated in cytotoxicity and characteristic of effector memory T cells, including CCL4, GNLY and NKG7. The 6-month clinical response to ICB in patients with MM is associated with the large CD8 + T cell clone count 21 d after treatment and agnostic to clonal specificity, suggesting that post-ICB peripheral CD8 + clonality can provide information regarding long-term treatment response and, potentially, facilitate treatment stratification.

Cancer treatment by immune checkpoint blockade (ICB) can bring long-lasting clinical benefits, but only a fraction of patients respond to treatment. To predict ICB response, we developed TIDE, a computational method to model two primary mechanisms of tumor immune evasion: the induction of T cell dysfunction in tumors with high infiltration of cytotoxic T lymphocytes (CTL) and the prevention of T cell infiltration in tumors with low CTL level. We identified signatures of T cell dysfunction from large tumor cohorts by testing how the expression of each gene in tumors interacts with the CTL infiltration level to influence patient survival. We also modeled factors that exclude T cell infiltration into tumors using expression signatures from immunosuppressive cells. Using this framework and pre-treatment RNA-Seq or NanoString tumor expression profiles, TIDE predicted the outcome of melanoma patients treated with first-line anti-PD1 or anti-CTLA4 more accurately than other biomarkers such as PD-L1 level and mutation load. TIDE also revealed new candidate ICB resistance regulators, such as SERPINB9, demonstrating utility for immunotherapy research.

Recent studies have linked elevated tumor aneuploidy to anti-tumor immune suppression and adverse survival following immunotherapy. Herein, we provide supportive evidence for tumor aneuploidy as a biomarker of response to immunotherapy in patients with non-small cell lung cancer (NSCLC). We identify a dose–response relationship between aneuploidy score and patient outcomes. In two independent NSCLC cohorts (n = 659 patients), we demonstrate a novel association between elevated aneuploidy and non-smoking-associated oncogenic driver mutations. Lastly, we report enrichment of TERT amplification and immune-suppressive phenotypes of highly aneuploid NSCLC. Taken together, our findings emphasize a potentially critical role for tumor aneuploidy in guiding immunotherapy treatment strategies. [ABSTRACT FROM AUTHOR]

The tumor microenvironment demonstrates great immunophenotypic heterogeneity, which has been leveraged in traditional immune-hot/cold tumor categorization based on the abundance of intra-tumoral immune cells. By incorporating the spatial immune contexture, the tumor immunophenotype was further elaborated into immune-inflamed, immune-excluded, and immune-desert. However, the mechanisms underlying these different immune phenotypes are yet to be comprehensively elucidated. In this review, we discuss how tumor cells and the tumor microenvironment interact collectively to shape the immune landscape from the perspectives of tumor cells, immune cells, the extracellular matrix, and cancer metabolism, and we summarize potential therapeutic options according to distinct immunophenotypes for personalized precision medicine. [ABSTRACT FROM AUTHOR]

Background: HIGD1B (HIG1 Hypoxia Inducible Domain Family Member 1B) is a protein-coding gene linked to the occurrence and progression of various illnesses. However, its precise function in gastric cancer (GC) remains unclear. Methods: The expression of HIGD1B is determined through the TCGA and GEO databases and verified using experiments. The association between HIGD1B and GC patients' prognosis was analyzed via the Kaplan-Meier (K-M) curve. Subsequently, the researchers utilized ROC curves to assess the diagnostic capacity of HIGD1B and employed COX analysis to investigate risk factors for GC. The differentially expressed genes (DEGs) were then subjected to functional enrichment analysis, and a nomogram was generated to forecast the survival outcome and probability of GC patients. Additionally, we evaluated the interaction between HIGD1B and the immune cell infiltration and predicted the susceptibility of GC patients to therapy. Results: HIGD1B is markedly elevated in GC tissue and cell lines, and patients with high HIGD1B expression have a poorer outcome. In addition, HIGD1B is related to distinct grades, stages, and T stages. The survival ROC curves of HIGD1B and nomogram for five years were 0.741 and 0.735, suggesting appropriate levels of diagnostic efficacy. According to Cox regression analysis, HIGD1B represents a separate risk factor for the prognosis of gastric cancer (p<0.01). GSEA analysis demonstrated that the HIGD1B is closely related to cancer formation and advanced pathways. Moreover, patients with high HIGD1B expression exhibited a higher level of Tumor-infiltration immune cells (TIICs) and were more likely to experience immune escape and drug resistance after chemotherapy and immunotherapy. Conclusion: This study explored the potential mechanisms and diagnostic and prognostic utility of HIGD1B in GC, as well as identified HIGD1B as a valuable biomarker and possible therapeutic target for GC. [ABSTRACT FROM AUTHOR]

Background: Immune checkpoint inhibitors (ICIs) have revolutionized gastrointestinal cancer treatment, yet the absence of reliable biomarkers hampers precise patient response prediction. Methods: We developed and validated a genomic mutation signature (GMS) employing a novel artificial intelligence network to forecast the prognosis of gastrointestinal cancer patients undergoing ICIs therapy. Subsequently, we explored the underlying immune landscapes across different subtypes using multiomics data. Finally, UMI-77 was pinpointed through the analysis of drug sensitization data from the Genomics of Drug Sensitivity in Cancer (GDSC) database. The sensitivity of UMI-77 to the AGS and MKN45 cell lines was evaluated using the cell counting kit-8 (CCK8) assay and the plate clone formation assay. Results: Using the artificial intelligence network, we developed the GMS that independently predicts the prognosis of gastrointestinal cancer patients. The GMS demonstrated consistent performance across three public cohorts and exhibited high sensitivity and specificity for 6, 12, and 24-month overall survival (OS) in receiver operating characteristic (ROC) curve analysis. It outperformed conventional clinical and molecular features. Low-risk samples showed a higher presence of cytolytic immune cells and enhanced immunogenic potential compared to high-risk samples. Additionally, we identified the small molecule compound UMI-77. The half-maximal inhibitory concentration (IC50) of UMI-77 was inversely related to the GMS. Notably, the AGS cell line, classified as high-risk, displayed greater sensitivity to UMI-77, whereas the MKN45 cell line, classified as low-risk, showed less sensitivity. Conclusion: The GMS developed here can reliably predict survival benefit for gastrointestinal cancer patients on ICIs therapy. [ABSTRACT FROM AUTHOR]

The past decade has witnessed a revolution in cancer treatment, shifting from conventional drugs (chemotherapies) towards targeted molecular therapies and immune-based therapies, in particular immune-checkpoint inhibitors (ICIs). These immunotherapies release the host's immune system against the tumor and have shown unprecedented durable remission for patients with cancers that were thought incurable, such as metastatic melanoma, metastatic renal cell carcinoma (RCC), microsatellite instability (MSI) high colorectal cancer and late stages of non-small cell lung cancer (NSCLC). However, about 80% of the patients fail to respond to these immunotherapies and are therefore left with other less effective and potentially toxic treatments. Identifying and understanding the mechanisms that enable cancerous cells to adapt to and eventually overcome therapy can help circumvent resistance and improve treatment. In this review, we describe the recent discoveries on the oncoimmunological processes which govern the tumor microenvironment and their impact on the resistance to PD-1/PD-L1 checkpoint blockade. [ABSTRACT FROM AUTHOR]

Background: Patients with lung adenocarcinoma (LUAD) often develop a poor prognosis. Currently, researches on prognostic and immunotherapeutic capacity of aneuploidy-related genes in LUAD are limited. Methods: Genes related to aneuploidy were screened based on bulk RNA sequencing data from public databases using Spearman method. Next, univariate Cox and Lasso regression analyses were performed to establish an aneuploidy-related riskscore (ARS) model. Results derived from bioinformatics analysis were further validated using cellular experiments. In addition, typical LUAD cells were identified by subtype clustering, followed by SCENIC and intercellular communication analyses. Finally, ESTIMATE, ssGSEA and CIBERSORT algorithms were employed to analyze the potential relationship between ARS and tumor immune environment. Results: A five-gene ARS signature was developed. These genes were abnormally high-expressed in LUAD cell lines, and in particular the high expression of CKS1B promoted the proliferative, migratory and invasive phenotypes of LUAD cell lines. Low ARS group had longer overall survival time, higher degrees of inflammatory infiltration, and could benefit more from receiving immunotherapy. Patients in low ASR group responded more actively to traditional chemotherapy drugs (Erlotinib and Roscovitine). The scRNA-seq analysis annotated 17 cell subpopulations into seven cell clusters. Core transcription factors (TFs) such as CREB3L1 and CEBPD were enriched in high ARS cell group, while TFs such as BCLAF1 and UQCRB were enriched in low ARS cell group. CellChat analysis revealed that high ARS cell groups communicated with immune cells via SPP1 (ITGA4-ITGB1) and MK (MDK-NCl) signaling pathways. Conclusion: In this research, integrative analysis based on the ARS model provided a potential direction for improving the diagnosis and treatment of LUAD. [ABSTRACT FROM AUTHOR]

Simple Summary: Immunotherapy may be beneficial for pancreatic cancer (PC) patients with mismatch repair (MMR) deficiency. Although it is known that MMR deficiency (MMR-D) can result from mutations in MMR genes, the prevalence of these mutations and their impact on the formation of the MMR-D phenotype in PC have been insufficiently researched. Microsatellite instability (MSI) is a hallmark of MMR-D. Here, we estimated the frequency of germline and somatic mutations in the three MMR genes (MLH1, MSH2, and MSH6) in PC patients, estimated the prevalence of MSI, and assessed the relationship between MMR genes mutations and MSI status in PC. In our study of an unselected cohort of PC patients, we identified germline and somatic alterations in MMR genes, however these alterations did not contribute to the MMR-D phenotype. Our findings underscore the necessity of evaluating tumor MMR-D status in PC patients with confirmed Lynch syndrome when deciding whether to administer immunotherapy. Patients with pancreatic cancer (PC) showing mismatch repair (MMR) deficiency may benefit from immunotherapy. Microsatellite instability (MSI) is a hallmark of MMR deficiency (MMR-D). Here, we estimated the prevalence of MSI in PC, investigated germline and somatic mutations in the three MMR genes (MLH1, MSH2, and MSH6), and assessed the relationship between MMR genes mutations and MSI status in PC. Clinical specimens from PC patients were analyzed using targeted next-generation sequencing, including paired normal and tumor specimens from 155 patients, tumor-only specimens from 86 patients, and normal-only specimens from 379 patients. The MSI status of 235 PCs was assessed via PCR. Pathogenic/likely pathogenic (P/LP) germline variants in the MMR genes were identified in 1.1% of patients, while somatic variants were found in 2.6% of patients. No MSI-H tumors were detected. One patient carried two variants (P (VAF = 0.57) and LP (VAF = 0.25)) simultaneously; however, their germline/somatic status remains unknown due to the investigation focusing solely on the tumor and MSI analysis was not performed for this patient. MSI is rare in PC, even in tumors with MMR genes mutations. Our findings underscore the importance of assessing tumor MMR-D status in PC patients with confirmed Lynch syndrome when deciding whether to prescribe immunotherapy. [ABSTRACT FROM AUTHOR]

Simple Summary: This study addresses the challenge of interpreting the efficacy of immunotherapy in biliary tract cancer (BTC) in terms of overall survival (OS). Traditional methods often rely on the proportional hazard assumption, which may not hold in this context. Instead, we performed a meta-analysis of available phase 3 trials using restricted median survival time (RMST) to measure temporal benefits, providing a clearer picture of the real effects of immunotherapy-based regimens. By incorporating anti-PD-1/anti-PD-L1 agents, our analysis confirmed improvements in estimated mean OS and progression-free survival (PFS) at 24 months, as indicated by RMST, of 1.21 (95% CI: 0.49–1.93) and 1.31 (95% CI: 0.66–1.96) months, respectively. This approach not only offers a more nuanced understanding of clinical benefits, but also aids healthcare providers and patients in making informed decisions about treatment options, emphasizing a methodology that can adapt to the complexities of data. Background: For biliary tract cancer (BTC), the addition of immunotherapy (durvalumab or pembrolizumab) to gemcitabine and cisplatin (GemCis) significantly improved overall survival (OS) in phase 3 clinical trials (RCTs). However, the interpretation and magnitude of the treatment effect is challenging because OS Kaplan–Meier curves violate the proportional hazards (PH) assumption. Analysis using restricted mean survival time (RMST) allows quantification of the benefits in the absence of PH. This systematic review and meta-analysis aims to assess the benefit of immunotherapy-based regimens for OS at 24 months using RMST analysis. Methods: A systematic review was conducted using studies published up to 8 November 2023. Only phase 3 RCTs evaluating the use of anti-PD-1/PD-L1 combined with GemCis and reporting OS were included. KM curves for OS were digitized, and the data were reconstructed. A meta-analysis for OS by RMST at 24 months was performed. Results: A total of 1754 participants from the TOPAZ-1 and KEYNOTE-966 trials were included. In TOPAZ-1, RMSTs at 24 months were 13.52 (7.92) and 12.21 (7.22) months with GemCis plus durvalumab and GemCis alone, respectively. In KEYNOTE-966, RMSTs at 24 months were 13.60 (7.76) and 12.45 (7.73) months with GemCis plus pembrolizumab and GemCis alone, respectively. Immunotherapy-based regimens showed a mean OS difference at 24 months by an RMST of 1.21 months [(95% CI: 0.49–1.93), p < 0.001, I2 = 0%]. Conclusions: Immunotherapy-based regimens improve OS in advanced BTC. Given this magnitude of benefit, it is essential to weigh up individual patient factors, preferences, and potential risks. RMST analysis provides valuable information to patients and physicians, facilitating decision-making in a value-based medical environment. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibitors (ICIs) represent a groundbreaking advance in the treatment of malignancies such as melanoma and non-small cell lung cancer, showcasing substantial therapeutic benefits. Nonetheless, the efficacy of ICIs is limited to a small subset of patients, primarily benefiting those with "hot" tumors characterized by significant immune infiltration. The challenge of converting "cold" tumors, which exhibit minimal immune activity, into "hot" tumors to enhance their responsiveness to ICIs is a critical and complex area of current research. Central to this endeavor is the activation of the cGAS-STING pathway, a pivotal nexus between innate and adaptive immunity. This pathway's activation promotes the production of type I interferon (IFN) and the recruitment of CD8+ T cells, thereby transforming the tumor microenvironment (TME) from "cold" to "hot". This review comprehensively explores the cGAS-STING pathway's role in reconditioning the TME, detailing the underlying mechanisms of innate and adaptive immunity and highlighting the contributions of various immune cells to tumor immunity. Furthermore, we delve into the latest clinical research on STING agonists and their potential in combination therapies, targeting this pathway. The discussion concludes with an examination of the challenges facing the advancement of promising STING agonists in clinical trials and the pressing issues within the cGAS-STING signaling pathway research. [ABSTRACT FROM AUTHOR]

Simple Summary: The majority of cases of colorectal cancer occur in those over the age of 65. Treatment of colorectal cancer in older adults warrants specific considerations due to the effects of aging on comorbidities, functional and cognitive status, and socioeconomic factors. Several recent advances have been made to improve oncological outcomes and reduce toxicities with colorectal cancer treatments in both localized and metastatic disease settings. This review highlights the importance of comprehensive geriatric assessment and provides recommendations to guide the management of older adults with colorectal cancer. It summarizes prospective data from recently reported clinical trials focused on older adults. Other recommendations must at times rely on extrapolations and post hoc analyses due to the underrepresentation of older adults in colorectal cancer trials. This review should also, therefore, serve as a call to action for the field to increase the representation of this substantial and often vulnerable group of patients in future colorectal cancer trials. Colorectal cancer (CRC) poses a significant global health challenge. Notably, the risk of CRC escalates with age, with the majority of cases occurring in those over the age of 65. Despite recent progress in tailoring treatments for early and advanced CRC, there is a lack of prospective data to guide the management of older patients, who are frequently underrepresented in clinical trials. This article reviews the contemporary landscape of managing older individuals with CRC, highlighting recent advancements and persisting challenges. The role of comprehensive geriatric assessment is explored. Opportunities for treatment escalation/de-escalation, with consideration of the older adult's fitness level. are reviewed in the neoadjuvant, surgical, adjuvant, and metastatic settings of colon and rectal cancers. Immunotherapy is shown to be an effective treatment option in older adults who have CRC with microsatellite instability. Promising new technologies such as circulating tumor DNA and recent phase III trials adding later-line systemic therapy options are discussed. Clinical recommendations based on the data available are summarized. We conclude that deliberate efforts to include older individuals in future colorectal cancer trials are essential to better guide the management of these patients in this rapidly evolving field. [ABSTRACT FROM AUTHOR]

Background: Immunotherapy has emerged as a potent clinical approach for cancer treatment, but only subsets of cancer patients can benefit from it. Targeting lactate metabolism (LM) in tumor cells as a method to potentiate anti-tumor immune responses represents a promising therapeutic strategy. Methods: Public single-cell RNA-Seq (scRNA-seq) cohorts collected from patients who received immunotherapy were systematically gathered and scrutinized to delineate the association between LM and the immunotherapy response. A novel LM-related signature (LM.SIG) was formulated through an extensive examination of 40 pan-cancer scRNA-seq cohorts. Then, multiple machine learning (ML) algorithms were employed to validate the capacity of LM.SIG for immunotherapy response prediction and survival prognostication based on 8 immunotherapy transcriptomic cohorts and 30 The Cancer Genome Atlas (TCGA) pan-cancer datasets. Moreover, potential targets for immunotherapy were identified based on 17 CRISPR datasets and validated via in vivo and in vitro experiments. Results: The assessment of LM was confirmed to possess a substantial relationship with immunotherapy resistance in 2 immunotherapy scRNA-seq cohorts. Based on large-scale pan-cancer data, there exists a notably adverse correlation between LM.SIG and anti-tumor immunity as well as imbalance infiltration of immune cells, whereas a positive association was observed between LM.SIG and pro-tumorigenic signaling. Utilizing this signature, the ML model predicted immunotherapy response and prognosis with an AUC of 0.73/0.80 in validation sets and 0.70/0.87 in testing sets respectively. Notably, LM.SIG exhibited superior predictive performance across various cancers compared to published signatures. Subsequently, CRISPR screening identified LDHA as a pan-cancer biomarker for estimating immunotherapy response and survival probability which was further validated using immunohistochemistry (IHC) and spatial transcriptomics (ST) datasets. Furthermore, experiments demonstrated that LDHA deficiency in pancreatic cancer elevated the CD8+ T cell antitumor immunity and improved macrophage antitumoral polarization, which in turn enhanced the efficacy of immunotherapy. Conclusions: We unveiled the tight correlation between LM and resistance to immunotherapy and further established the pan-cancer LM.SIG, holds the potential to emerge as a competitive instrument for the selection of patients suitable for immunotherapy. [ABSTRACT FROM AUTHOR]

Background: T cell exhaustion in the tumor microenvironment has been demonstrated as a substantial contributor to tumor immunosuppression and progression. However, the correlation between T cell exhaustion and osteosarcoma (OS) remains unclear. Methods: In our present study, single-cell RNA-seq data for OS from the GEO database was analysed to identify CD8+ T cells and discern CD8+ T cell subsets objectively. Subgroup differentiation trajectory was then used to pinpoint genes altered in response to T cell exhaustion. Subsequently, six machine learning algorithms were applied to develop a prognostic model linked with T cell exhaustion. This model was subsequently validated in the TARGETs and Meta cohorts. Finally, we examined disparities in immune cell infiltration, immune checkpoints, immune-related pathways, and the efficacy of immunotherapy between high and low TEX score groups. Results: The findings unveiled differential exhaustion in CD8+ T cells within the OS microenvironment. Three genes related to T cell exhaustion (RAD23A, SAC3D1, PSIP1) were identified and employed to formulate a T cell exhaustion model. This model exhibited robust predictive capabilities for OS prognosis, with patients in the low TEX score group demonstrating a more favorable prognosis, increased immune cell infiltration, and heightened responsiveness to treatment compared to those in the high TEX score group. Conclusion: In summary, our research elucidates the role of T cell exhaustion in the immunotherapy and progression of OS, the prognostic model constructed based on T cell exhaustion-related genes holds promise as a potential method for prognostication in the management and treatment of OS patients. [ABSTRACT FROM AUTHOR]

Background: Recently, long non-coding RNAs (lncRNAs) have been demonstrated as essential roles in tumor immune microenvironments (TIME). Nevertheless, researches on the clinical significance of TIME-related lncRNAs are limited in lung adenocarcinoma (LUAD). Methods: Single-cell RNA sequencing and bulk RNA sequencing data are integrated to identify TIME-related lncRNAs. A total of 1368 LUAD patients are enrolled from 6 independent datasets. An integrative machine learning framework is introduced to develop a TIME-related lncRNA signature (TRLS). Results: This study identified TIME-related lncRNAs from integrated analysis of single‑cell and bulk RNA sequencing data. According to these lncRNAs, a TIME-related lncRNA signature was developed and validated from an integrative procedure in six independent cohorts. TRLS exhibited a robust and reliable performance in predicting overall survival. Superior prediction performance barged TRLS to the forefront from comparison with general clinical features, molecular characters, and published signatures. Moreover, patients with low TRLS displayed abundant immune cell infiltration and active lipid metabolism, while patients with high TRLS harbored significant genomic alterations, high PD-L1 expression, and elevated DNA damage repair (DDR) relevance. Notably, subclass mapping analysis of nine immunotherapeutic cohorts demonstrated that patients with high TRLS were more sensitive to immunotherapy. Conclusions: This study developed a promising tool based on TIME-related lncRNAs, which might contribute to tailored treatment and prognosis management of LUAD patients. [ABSTRACT FROM AUTHOR]

Simple Summary: In a comprehensive analysis of phase 3 clinical trials, including the two FLAIR sub-studies, ECOG1912, and the CLL13 trials, we assessed the impact of first-line treatments with targeted agents (TAs), or fludarabine, cyclophosphamide, and rituximab (FCR)-based chemo-immunotherapy (CIT), on overall survival (OS) compared to age- and sex-matched individuals in the general population. TAs demonstrated a higher 5-year restricted mean survival time (RMST) (58.1 months; 95% CI: 57.4 to 58.8) compared to CIT (5-year RMST, 56.9 months; 95% CI: 56.7–58.2). Moreover, the comparison with age- and gender-matched general populations (AGMGP) suggested that TAs may mitigate CLL's impact on OS during the first five years post-treatment initiation. In contrast, CLL patients treated with FCR exhibited sustained OS differences compared to both the Italian and US AGMGP cohorts. These results support TAs as the preferred first-line treatment for younger/fit CLL patients but imply the need for a careful interpretation due to variations in patient selection criteria and clinical profiles across trials. Longer follow-up is essential to assess the survival improvement of younger CLL patients treated with TAs relative to the AGMGP. To assess the impact of first-line treatment with targeted agents (TAs) or fludarabine, cyclophosphamide, and rituximab (FCR)-based chemo-immunotherapy (CIT) on overall survival (OS) compared to age- and sex-matched individuals in the general population, we conducted an aggregated analysis of phase 3 clinical trials, including the two FLAIR sub-studies, ECOG1912, and CLL13 trials. The restricted mean survival time (RMST), an alternative measure in outcome analyses capturing OS changes over the entire history of the disease, was used to minimize biases associated with the short follow-up time of trials. Patients treated with TAs demonstrated a higher 5-year RMST (58.1 months; 95% CI: 57.4 to 58.8) compared to those treated with CIT (5-year RMST, 56.9 months; 95% CI: 56.7–58.2). Furthermore, the OS comparison of treatment groups with the AGMGP suggests that TAs may mitigate the impact of CLL on OS during the first five years post-treatment initiation. In summary, the 5-year RMST difference was −0.4 months (95% CI: −0.8 to 0.2; p = 0.10) when comparing CLL patients treated with TAs to the Italian age- and gender-matched general population (AGMGP). A similar trend was observed when CLL patients treated with TAs were compared to the US AGMGP (5-year RMST difference, 0.3 months; 95% CI: −0.1 to 0.9; p = 0.12). In contrast, CLL patients treated with FCR exhibited sustained OS differences when compared to both the Italian cohort (5-year RMST difference: −1.6 months; 95% CI: −2.4 to −0.9; p < 0.0001) and the US AGMGP cohort (5-year RMST difference: −0.9 months; 95% CI: −1.7 to −0.2; p = 0.015). Although these results support TAs as the preferred first-line treatment for younger CLL patients, it is crucial to acknowledge that variations in patient selection criteria and clinical profiles across clinical trials necessitate a cautious interpretation of these findings that should be viewed as directional and hypothesis-generating. A longer follow-up is needed to assess the survival improvement of younger CLL patients treated with TAs relative to the AGMGP. [ABSTRACT FROM AUTHOR]

Background: Atezolizumab + bevacizumab represent the current standard of care for first-line treatment of advanced hepatocellular carcinoma (HCC). However, direct comparison with other combination treatments including immune checkpoint inhibitors (ICI) + tyrosine kinase inhibitors (TKIs) are lacking. Objectives: This network meta-analysis (NMA) aims to indirectly compare the efficacy and the safety of first-line systemic therapies for unresectable advanced HCC. Method: A literature search of MEDLINE, Embase, and SCOPUS databases was conducted up to October 31, 2022. Phase 3 randomized controlled trials (RCTs) testing TKIs, including sorafenib and lenvatinib, or ICIs reporting overall survival (OS) and progression-free survival (PFS) were included. Individual survival data were extracted from OS and PFS curves to calculate restricted mean survival time. A Bayesian NMA was performed to compare treatments in terms of efficacy (15- and 30-month OS, 6-month PFS) and safety, represented by grade ≥3 (severe) adverse events (SAEs). The incremental safety-effectiveness ratio as measure of net health benefit was calculated as the difference in SAE probability divided by survival difference between the 2 most effective treatments. Results: Nine RCTs enrolling 6,600 patients were included. Atezolizumab plus bevacizumab showed the highest probability (88%) of achieving the 30-month OS landmark. Lenvatinib showed a probability of 86% of achieving best PFS outcomes. ICI monotherapies ranked as most tolerable. Atezolizumab plus bevacizumab showed the best net health benefit for OS, compared to durvalumab plus tremelimumab. When evaluating the net health benefit for PFS, at a willingness-to-risk threshold of 10% of SAEs for life-month gained, atezolizumab plus bevacizumab was favoured in 78% of cases, while at threshold of 30% of SAEs for life-month gained, lenvatinib was favoured in 76% of cases. Conclusions: Atezolizumab plus bevacizumab is the best treatment in terms of net benefit and therefore it should be recommended as standard of care. Compared to atezolizumab plus bevacizumab, lenvatinib monotherapy had the best net benefit for PFS when physicians and patients are available to accept a higher risk of toxicity. [ABSTRACT FROM AUTHOR]

Simple Summary: A subset of advanced melanoma patients have a mutant BRAF protein. Two classes of therapy options are available to these patients, but it is unclear which is more effective in this population. We analyzed patient samples treated with either immunotherapy or BRAF-targeted therapy and found that those treated with immunotherapy had notably better outcomes. We further analyzed if aneuploidy or cGAS expression could act as a biomarker for how patients responded to either treatment. We found no association between aneuploidy and clinical outcomes. We observed that cGAS expression may correlate with outcome, but it appears to be a nuanced relationship and requires more study. BRAF-mutant melanoma patients can be treated with targeted therapy or immunotherapies, and it is not clear which should be provided first. Targeted treatments do not work in up to one-third of cases, while immunotherapies may only be effective in up to 60% and come with a high risk of immune-related side effects. Determining which treatment to provide first is thus of critical importance. Recent studies suggest that chromosomal instability and aneuploidy and cyclic GMP-AMP synthase (cGAS) can act as biomarkers for cancer severity and patient outcome. Neither potential biomarker has been extensively studied in melanoma. We examined 20 BRAF-mutant melanomas treated with immunotherapy or targeted therapy and measured chromosomal aneuploidy and cGAS expression levels. Treatment type, aneuploidy, and cGAS expression were correlated with progression-free survival (PFS) in these patients. Those treated with immunotherapy first had significantly better outcomes than those treated with targeted therapy, suggesting immunotherapy should be strongly considered as the first-line therapy for patients bearing BRAF-mutant melanoma. We found that there was no correlation of aneuploidy with outcome while there was some positive correlation of cGAS levels with PFS. Further studies are needed to confirm these findings and to test other potential biomarkers. [ABSTRACT FROM AUTHOR]

Simple Summary: Lynch syndrome (LS) stands as the predominant inherited cancer condition at present. Currently, surveillance is based on genotype-driven strategies and mostly comprises both invasive and non-invasive medical assessments for early diagnosis. Effective preventive strategies for interrupting the biological sequence of cancer development are yet to be established. Recent findings from randomized controlled trials indicate potential preventive functions of resistant starch and/or aspirin in Lynch syndrome. The use of immunogenic frameshift peptides for vaccination appears to be a promising approach for both treating and preventing Lynch syndrome-associated cancers, based on pre-clinical and early phase 1/2a studies. Background and Aims: Lynch syndrome (LS) is currently one of the most prevalent hereditary cancer conditions, accounting for 3% of all colorectal cancers and for up to 15% of those with DNA mismatch repair (MMR) deficiency, and it was one of the first historically identified. The understanding of the molecular carcinogenesis of LS tumors has progressed significantly in recent years. We aim to review the most recent advances in LS research and explore genotype-based approaches in surveillance, personalized cancer prevention, and treatment strategies. Methods: PubMed was searched to identify relevant studies, conducted up to December 2023, investigating molecular carcinogenesis in LS, surveillance strategies, cancer prevention, and treatment in LS tumors. Results: Multigene panel sequencing is becoming the benchmark in the diagnosis of LS, allowing for the detection of a pathogenic constitutional variant in one of the MMR genes. Emerging data from randomized controlled trials suggest possible preventive roles of resistant starch and/or aspirin in LS. Vaccination with immunogenic frameshift peptides appears to be a promising approach for both the treatment and prevention of LS-associated cancers, as evidenced by pre-clinical and preliminary phase 1/2a studies. Conclusions: Although robust diagnostic algorithms, including prompt testing of tumor tissue for MMR defects and referral for genetic counselling, currently exist for suspected LS in CRC patients, the indications for LS screening in cancer-free individuals still need to be refined and standardized. Investigation into additional genetic and non-genetic factors that may explain residual rates of interval cancers, even in properly screened populations, would allow for more tailored preventive strategies. [ABSTRACT FROM AUTHOR]

Introduction: There is debate on which are the best surrogate endpoint and metric to capture treatment effect on overall survival (OS) in RCTs testing immune-checkpoint inhibitors (ICIs). Methods: We systematically searched for RCTs testing ICIs in patients with advanced solid tumors. Inclusion criteria were: RCTs i) assessing PD-(L)1 and CTLA-4 inhibitors either as monotherapy or in combination with another ICI, and/or targeted therapy, and/or chemotherapy, in patients with advanced solid tumors; ii) randomizing at least 100 patients. We performed a meta-analysis of RCTs to compare the surrogacy value of PFS and modified-PFS (mPFS) for OS in RCTs testing ICIs, when the treatment effect is measured by the hazard ratio (HR) for OS, and by the HR and the ratio of restricted mean survival time (rRMST) for PFS and mPFS. Results: 61 RCTs (67 treatment comparisons and 36,034 patients) were included in the analysis. In comparisons testing ICI plus chemotherapy, HRPFS and HRmPFS both had a strong surrogacy value (R2 = 0.74 and R2 = 0.81, respectively). In comparisons testing ICI as monotherapy, HRPFS was the best surrogate, although having a moderate correlation (R2 = 0.58). In comparisons testing ICI plus other treatment(s), the associations were very weak for all the surrogate endpoints and treatment effect measures, with R2 ranging from 0.01 to 0.22. Conclusion: In RCTs testing ICIs, the value of potential surrogates for HROS was strongly affected by the type of treatment(s) tested. The evidence available supports HRPFS as the best surrogate, and disproves the use of alternative endpoints, such as the mPFS, or treatment effect measures, such as the RMST. [ABSTRACT FROM AUTHOR]

Introduction: Identifying which patient may benefit from immunotherapeutic early-phase clinical trials is an unmet need in drug development. Among several proposed prognostic scores, none has been validated in patients receiving immunomodulating agents (IMAs)-based combinations. Patients and methods: We retrospectively collected data of 208 patients enrolled in early-phase clinical trials investigating IMAs at our Institution, correlating clinical and blood-based variables with overall survival (OS). A retrospective cohort of 50 patients treated with IMAs at Imperial College (Hammersmith Hospital, London, UK) was used for validation. Results: A total of 173 subjects were selected for analyses. Most frequent cancers included non-small cell lung cancer (26%), hepatocellular carcinoma (21.5%) and glioblastoma (13%). Multivariate analysis (MVA) revealed 3 factors to be independently associated with OS: line of treatment (second and third vs subsequent, HR 0.61, 95% CI 0.40-0.93, p 0.02), serum albumin as continuous variable (HR 0.57, 95% CI 0.36-0.91, p 0.02) and number of metastatic sites (<3 vs =3, HR 0.68, 95% CI 0.48-0.98, p 0.04). After splitting albumin value at the median (3.84 g/dL), a score system was capable of stratifying patients in 3 groups with significantly different OS (p<0.0001). Relationship with OS reproduced in the external cohort (p=0.008). Then, from these factors we built a nomogram. Conclusions: Prior treatment, serum albumin and number of metastatic sites are readily available prognostic traits in patients with advanced malignancies participating into immunotherapy early-phase trials. Combination of these factors can optimize patient selection at study enrollment, maximizing therapeutic intent. [ABSTRACT FROM AUTHOR]

Simple Summary: Thrombotic events are a common problem for lung cancer patients. Compared to other types of cancer, lung cancer patients are more likely to experience blood clots at any stage of their disease. Some newer cancer treatments, like immunotherapy, can also raise the risk of thrombosis. Two different categories of drugs that prevent the formation of blood clots, low-molecular-weight heparins (LMWHs) and direct oral anticoagulants (DOACs), have similar benefits in walking patients. The choice of which drug to use and when should be personalized based on the characteristics of the patient, the type of lung cancer, as well as recent treatments, such as surgery, chemotherapy or immunotherapy. The use of models that aim to predict the risk of blood clots for each patient may help physicians choose when to start treatment with anticoagulation drugs. Cancer-associated thrombosis (CAT) is a common complication in lung cancer patients. Lung cancer confers an increased risk of thrombosis compared to other solid malignancies across all stages of the disease. Newer treatment agents, including checkpoint immunotherapy and targeted agents, may further increase the risk of CAT. Different risk-assessment models, such as the Khorana Risk Score, and newer approaches that incorporate genetic risk factors have been used in lung cancer patients to evaluate the risk of thrombosis. The management of CAT is based on the results of large prospective trials, which show similar benefits to low-molecular-weight heparins (LMWHs) and direct oral anticoagulants (DOACs) in ambulatory patients. The anticoagulation agent and duration of therapy should be personalized according to lung cancer stage and histology, the presence of driver mutations and use of antineoplastic therapy, including recent curative lung surgery, chemotherapy or immunotherapy. Treatment options should be evaluated in the context of the COVID-19 pandemic, which has been shown to impact the thrombotic risk in cancer patients. This review focuses on the epidemiology, pathophysiology, risk factors, novel predictive scores and management of CAT in patients with active lung cancer, with a focus on immune checkpoint inhibitors. [ABSTRACT FROM AUTHOR]

Background: Immune checkpoint inhibitors (ICIs) are a therapeutic strategy for various cancers although only a subset of patients respond to the therapy. Identifying patients more prone to respond to ICIs may increase the therapeutic benefit and allow studying new approaches for resistant patients. Methods: We analyzed the TCGA cohort of HNSCC patients in relation to their activation of 26 immune gene expression signatures, as well as their cell type composition, in order to define signaling pathways associated with resistance to ICIs. Results were validated on two cohorts of 102 HNSCC patients and 139 HNSCC patients under treatment with PD-L1 inhibitors, respectively, and a cohort of 108 HNSCC HPV negative patients and by in vitro experiments in HNSCC cell lines. Results: We observed a significant association between the gene set and TP53 gene status and OS and PFS of HNSCC patients. Surprisingly, the presence of a TP53 mutation together with another co-driver mutation was associated with significantly higher levels of the immune gene expression, in comparison to tumors in which the TP53 gene was mutated alone. In addition, the higher level of TP53 mutated-dependent MYC signature was associated with lower levels of the immune gene expression signature. In vitro and three different patient cohorts validation analyses corroborated these findings. Conclusions: Immune gene signature sets associated with TP53 status and co-mutations classify with more accuracy HNSCC patients. These biomarkers may be easily implemented in clinical setting. [ABSTRACT FROM AUTHOR]

Immune checkpoint blockade (ICB) therapies, that is, using monoclonal antibodies to reinvigorate tumor-reactive, antigen-specific T cells from the inhibitory effects of CTLA-4, PD-1 and PD-L1 immune checkpoints, have revolutionized the therapeutic landscape of modern oncology. However, only a subset of patients can benefit from the ICB therapy. Biomarkers associated with ICB response, resistance and prognosis have been subjected to intensive research in the past decade. Early studies focused on the analysis of tumor specimens and their residing microenvironment. However, biopsies can be challenging to obtain in clinical practice, and do not reflect the dynamic changes of immunological parameters during the ICB therapy. Recent studies have investigated profiles of antigen-specific T cells derived from the peripheral compartment using multi-omics approaches. By tracking the clonotype and diversity of tumor-reactive T cell receptor repertoire, these studies collectively establish that de novo priming of antigen-specific T cells in peripheral blood occurs throughout the course of ICB, whereas preexisting T cells prior to ICB are exhausted to various degrees. Here, we review what is known about ICB-induced T cell phenotypic and functional changes in cancer patients both within the tumor microenvironment and in the peripheral compartment. A better understanding of parameters influencing the response to ICBs will provide rationales for developing novel diagnostics and combinatorial therapeutic strategies to maximize the clinical efficacies of ICB therapies. [ABSTRACT FROM AUTHOR]

Simple Summary: Immunotherapy has become a very important treatment against several types of cancer. The clinical trials of immunotherapy have shown that these treatments present us with some novel challenges in terms of the methodology required to assess their efficacy and safety. In this article, we discuss what we consider to be the most important among those challenges and provide some suggestions to address them in the design and analysis of clinical trials of immunotherapy, especially with the class of treatments named "checkpoint inhibitors". In summary, the methodological aspects discussed in this article refer to definitions and implementation of efficacy endpoints, the evaluation of safety, and specific statistical issues that may require special attention in these trials. Immunotherapy with checkpoint inhibitors (CPIs) and cell-based products has revolutionized the treatment of various solid tumors and hematologic malignancies. These agents have shown unprecedented response rates and long-term benefits in various settings. These clinical advances have also pointed to the need for new or adapted approaches to trial design and assessment of efficacy and safety, both in the early and late phases of drug development. Some of the conventional statistical methods and endpoints used in other areas of oncology appear to be less appropriate in immuno-oncology. Conversely, other methods and endpoints have emerged as alternatives. In this article, we discuss issues related to trial design in the early and late phases of drug development in immuno-oncology, with a focus on CPIs. For early trials, we review the most salient issues related to dose escalation, use and limitations of tumor response and progression criteria for immunotherapy, the role of duration of response as an endpoint in and of itself, and the need to conduct randomized trials as early as possible in the development of new therapies. For late phases, we discuss the choice of primary endpoints for randomized trials, review the current status of surrogate endpoints, and discuss specific statistical issues related to immunotherapy, including non-proportional hazards in the assessment of time-to-event endpoints, alternatives to the Cox model in these settings, and the method of generalized pairwise comparisons, which can provide a patient-centric assessment of clinical benefit and be used to design randomized trials. [ABSTRACT FROM AUTHOR]

Background: lung adenocarcinoma (LUAD) remains one of the most common and lethal malignancies with poor prognosis. Programmed cell death (PCD) is an evolutionarily conserved cell suicide process that regulates tumorigenesis, progression, and metastasis of cancer cells. However, a comprehensive analysis of the role of PCD in LUAD is still unavailable. Methods: We analyzed multi-omic variations in PCD-related genes (PCDRGs) for LUAD. We used cross-validation of 10 machine learning algorithms (101 combinations) to synthetically develop and validate an optimal prognostic cell death score (CDS) model based on the PCDRGs expression profile. Patients were classified based on their median CDS values into the high and low-CDS groups. Next, we compared the differences in the genomics, biological functions, and tumor microenvironment of patients between both groups. In addition, we assessed the ability of CDS for predicting the response of patients from the immunotherapy cohort to immunotherapy. Finally, functional validation of key genes in CDS was performed. Results: We constructed CDS based on four PCDRGs, which could effectively and consistently stratify patients with LUAD (patients with high CDS had poor prognoses). The performance of our CDS was superior compared to 77 LUAD signatures that have been previously published. The results revealed significant genetic alterations like mutation count, TMB, and CNV were observed in patients with high CDS. Furthermore, we observed an association of CDS with immune cell infiltration, microsatellite instability, SNV neoantigens. The immune status of patients with low CDS was more active. In addition, CDS could be reliable to predict therapeutic response in multiple immunotherapy cohorts. In vitro experiments revealed that high DNA damage inducible transcript 4 (DDIT4) expression in LUAD cells mediated protumor effects. Conclusion: CDS was constructed based on PCDRGs using machine learning. This model could accurately predict patients' prognoses and their responses to therapy. These results provide new promising tools for clinical management and aid in designing personalized treatment strategies for patients with LUAD. [ABSTRACT FROM AUTHOR]

Simple Summary: Immune checkpoint blockades (ICBs) therapy has produced durable clinical responses in many cancer types, but only a fraction of patients can benefit from ICB treatment. Previous studies have reported multiple transcriptomic biomarkers to predict ICB responses and improve treatment precision in various cancer types. However, a timely and unbiased assessment of these biomarkers has yet to be conducted due to the lack of large-scale uniformly curated ICB-treated datasets. To address the needs, we developed ICB-Portal, a comprehensive resource about ICB including RNA-seq data of 29 datasets from public sources and standardized metadata of each study through a uniform pre-processing, 48 biomarker scores associated with ICB response, results of a systematic benchmark analysis evaluating the efficacy, and generalization ability for each biomarker in various scenarios such as different cancer types, anti-bodies, biopsy time, and combinatory treatments with other drugs by a standardized bioinformatics workflow and an online benchmark platform. Immune checkpoint blockades (ICBs) have revolutionized cancer therapy by inducing durable clinical responses, but only a small percentage of patients can benefit from ICB treatments. Many studies have established various biomarkers to predict ICB responses. However, different biomarkers were found with diverse performances in practice, and a timely and unbiased assessment has yet to be conducted due to the complexity of ICB-related studies and trials. In this study, we manually curated 29 published datasets with matched transcriptome and clinical data from more than 1400 patients, and uniformly preprocessed these datasets for further analyses. In addition, we collected 39 sets of transcriptomic biomarkers, and based on the nature of the corresponding computational methods, we categorized them into the gene-set-like group (with the self-contained design and the competitive design, respectively) and the deconvolution-like group. Next, we investigated the correlations and patterns of these biomarkers and utilized a standardized workflow to systematically evaluate their performance in predicting ICB responses and survival statuses across different datasets, cancer types, antibodies, biopsy times, and combinatory treatments. In our benchmark, most biomarkers showed poor performance in terms of stability and robustness across different datasets. Two scores (TIDE and CYT) had a competitive performance for ICB response prediction, and two others (PASS-ON and EIGS_ssGSEA) showed the best association with clinical outcome. Finally, we developed ICB-Portal to host the datasets, biomarkers, and benchmark results and to implement the computational methods for researchers to test their custom biomarkers. Our work provided valuable resources and a one-stop solution to facilitate ICB-related research. [ABSTRACT FROM AUTHOR]

Simple Summary: The current study investigated the potential use of fluorometric cfDNA quantification as a prognostic biomarker in advanced non-small cell lung cancer (NSCLC) patients treated with an Immune Checkpoint Blockade (ICB). Results showed that a cfDNA cut-off of 0.55 ng/µL before the ICB determines the overall survival of patients with a log rank p-value of 3.3 × 10−4. High cfDNA concentrations identify patients with advanced NSCLC who do not benefit from ICB. The determination of cfDNA is a simple test that could select a group of patients in whom new therapeutic strategies are needed. The present study aimed to investigate the potential of basal cell-free fluorometric DNA (cfDNA) quantification as a prognostic biomarker in advanced non-small cell lung cancer (NSCLC) patients treated with an Immune Checkpoint Blockade (ICB). A discovery and validation cohort of 61 and 31 advanced lung cancer patients treated with ICB were included in this study. Quantification of cfDNA concentration was performed before the start of the treatment and patients were followed up for a median of 34 (30–40) months. The prognostic predicted value of cfDNA was evaluated based on ROC, and Cox regression was conducted via univariate and multivariate analyses to estimate the hazard ratio. We observed that a cfDNA cut-off of 0.55 ng/µL before the ICB determines the overall survival of patients with a log rank p-value of 3.3 × 10−4. That represents median survivals of 3.8 vs. 17.5 months. Similar results were obtained in the validation cohort being the log rank p-value 3.8 × 10−2 with median survivals of 5.9 vs. 24.3. The univariate and multivariate analysis revealed that the cut-off of 0.55 ng/µL before ICB treatment was an independent predictive factor and was significantly associated with a better survival outcome. High cfDNA concentrations identify patients with advanced NSCLC who do not benefit from the ICB. The determination of cfDNA is a simple test that could select a group of patients in whom new therapeutic strategies are needed. [ABSTRACT FROM AUTHOR]

Circular RNAs (circRNAs) play important roles in the regulation of cancer. However, the clinical implications and regulatory networks of circRNAs in cancer patients receiving immune checkpoint blockades (ICB) have not been fully elucidated. Here, we characterize circRNA expression profiles in two independent cohorts of 157 ICB-treated advanced melanoma patients and reveal overall overexpression of circRNAs in ICB non-responders in both pre-treatment and early during therapy. Then, we construct circRNA-miRNA-mRNA regulatory networks to reveal circRNA-related signaling pathways in the context of ICB treatment. Further, we construct an ICB-related circRNA signature (ICBcircSig) score model based on progression-free survival-related circRNAs to predict immunotherapy efficacy. Mechanistically, the overexpression of ICBcircSig circTMTC3 and circFAM117B could increase PD-L1 expression via the miR-142-5p/PD-L1 axis, thus reducing T cell activity and leading to immune escape. Overall, our study characterizes circRNA profiles and regulatory networks in ICB-treated patients, and highlights the clinical utility of circRNAs as predictive biomarkers of immunotherapy. Circular RNAs are known to be linked to cancer regulation. Here, the authors identify a circular RNA signature associated with immune checkpoint response in melanoma. [ABSTRACT FROM AUTHOR]

Checkpoint inhibitors can be a highly effective antitumor therapy but only to a subset of patients, presumably due to immunotherapy resistance. Fluoxetine was recently revealed to inhibit the NLRP3 inflammasome, and NLRP3 inhibition could serve as a target for immunotherapy resistance. Therefore, we evaluated the overall survival (OS) in patients with cancer receiving checkpoint inhibitors combined with fluoxetine. A cohort study was conducted among patients diagnosed with lung, throat (pharynx or larynx), skin, or kidney/urinary cancer treated with checkpoint inhibitor therapy. Utilizing the Veterans Affairs Informatics and Computing Infrastructure, patients were retrospectively evaluated during the period from October 2015 to June 2021. The primary outcome was overall survival (OS). Patients were followed until death or the end of the study period. There were 2316 patients evaluated, including 34 patients who were exposed to checkpoint inhibitors and fluoxetine. Propensity score weighted Cox proportional hazards demonstrated a better OS in fluoxetine-exposed patients than unexposed (HR: 0.59, 95% CI 0.371–0.936). This cohort study among cancer patients treated with checkpoint inhibitor therapy showed a significant improvement in the OS when fluoxetine was used. Because of this study's potential for selection bias, randomized trials are needed to assess the efficacy of the association of fluoxetine or another anti-NLRP3 drug to checkpoint inhibitor therapy. [ABSTRACT FROM AUTHOR]

Cancer is one of the leading causes of death in the world; therefore, extensive research has been dedicated to exploring potential therapeutics, including immune checkpoint inhibitors (ICIs). Initially, programmed-death ligand-1 was the biomarker utilized to predict the efficacy of ICIs. However, its heterogeneous expression in the tumor microenvironment, which is critical to cancer progression, promoted the exploration of the tumor mutation burden (TMB). Research in various cancers, such as melanoma and lung cancer, has shown an association between high TMB and response to ICIs, increasing its predictive value. However, the TMB has failed to predict ICI response in numerous other cancers. Therefore, future research is needed to analyze the variations between cancer types and establish TMB cutoffs in order to create a more standardized methodology for using the TMB clinically. In this review, we aim to explore current research on the efficacy of the TMB as a biomarker, discuss current approaches to overcoming immunoresistance to ICIs, and highlight new trends in the field such as liquid biopsies, next generation sequencing, chimeric antigen receptor T-cell therapy, and personalized tumor vaccines. [ABSTRACT FROM AUTHOR]

Lung cancer is the leading cause of cancer‐related deaths worldwide. Surgery and chemoradiation are the standard of care in early stages of non‐small cell lung cancer (NSCLC), while immunotherapy is the standard of care in late‐stage NSCLC. The immune composition of the tumor microenvironment (TME) is recognized as an indicator for responsiveness to immunotherapy, although much remains unknown about its role in responsiveness to surgery or chemoradiation. In this pilot study, we characterized the NSCLC TME using mass cytometry (CyTOF) and bulk RNA sequencing (RNA‐Seq) with deconvolution of RNA‐Seq being performed by Kassandra, a recently published deconvolution tool. Stratification of patients based on the intratumoral abundance of B cells identified that the B‐cell rich patient group had increased expression of CXCL13 and greater abundance of PD1+ CD8 T cells. The presence of B cells and PD1+ CD8 T cells correlated positively with the presence of intratumoral tertiary lymphoid structures (TLS). We then assessed the predictive and prognostic utility of these cell types and TLS within publicly available stage 3 and 4 lung adenocarcinoma (LUAD) RNA‐Seq datasets. As previously described by others, pre‐treatment expression of intratumoral 12‐chemokine TLS gene signature is associated with progression free survival (PFS) in patients who receive treatment with immune checkpoint inhibitors (ICI). Notably and unexpectedly pre‐treatment percentages of intratumoral B cells are associated with PFS in patients who receive surgery, chemotherapy, or radiation. Further studies to confirm these findings would allow for more effective patient selection for both ICI and non‐ICI treatments. [ABSTRACT FROM AUTHOR]

In recent years, immune checkpoint inhibitors (ICIs) have revolutionized the treatment of patients with hepatocellular carcinoma (HCC). Following the positive results of the IMbrave150 trial, the combination of atezolizumab (an anti-PD-L1 antibody) and bevacizumab (an anti-VEGF antibody) became the standard of care frontline treatment for patients with advanced stage HCC. Several other trials evaluated immunotherapy in HCC, demonstrating that ICIs-based regimens are currently the most effective treatment strategies and expanding the therapeutic possibilities. Despite the unprecedent rates of objective tumor response, not all patients benefit from treatment with ICIs. Therefore, in order to select the appropriate therapy as well as to correctly allocate medical resources and avoid unnecessary treatment-related toxicities, there is great interest in identifying the predictive biomarkers of response or resistance to immunotherapy-based regimens. Immune classes of HCC, genomic signatures, anti-drug antibodies, and patient-related factors (e.g., etiology of liver disease, gut microbiota diversity) have been associated to the response to ICIs, but none of the proposed biomarkers have been translated into clinical practice so far. Considering the crucial importance of this topic, in this review we aim to summarize the available data on tumor and clinical features associated with the response or resistance of HCC to immunotherapies. [ABSTRACT FROM AUTHOR]

Simple Summary: DNA repair pathways play a crucial role in maintaining the stability of a cell's genetic material. When these pathways are defective, it can lead to genomic instability in cancer cells, which can increase their ability to stimulate an immune response. Inhibiting DNA damage response, the process that helps repair DNA damage, has been shown to increase the effectiveness of anticancer immunotherapies. In this review, we will explore how deficits in the DNA repair pathway can affect the immune system's ability to fight cancer. We will also examine clinical trials that have combined inhibition of DNA damage response with immune-oncology treatments. A better understanding of these pathways could help improve the effectiveness of cancer immunotherapies and other treatments for various types of cancer. Defects in DNA repair pathways can lead to genomic instability in multiple tumor types, which contributes to tumor immunogenicity. Inhibition of DNA damage response (DDR) has been reported to increase tumor susceptibility to anticancer immunotherapy. However, the interplay between DDR and the immune signaling pathways remains unclear. In this review, we will discuss how a deficiency in DDR affects anti-tumor immunity, highlighting the cGAS-STING axis as an important link. We will also review the clinical trials that combine DDR inhibition and immune-oncology treatments. A better understanding of these pathways will help exploit cancer immunotherapy and DDR pathways to improve treatment outcomes for various cancers. [ABSTRACT FROM AUTHOR]

Simple Summary: This study aims to compare effectiveness and cost profile in non-small-cell lung cancer (NSCLC) patients harboring synchronous brain metastases (BMs) who received non-chemo first-line systemic therapy with or without advanced radiotherapy (aRT). A total of 177 lung cancer patients, of whom 58 were treated with systemic treatment (either TKIs or pembrolizumab) plus aRT (STRT) and 119 with systemic treatment alone, were selected. The addition of aRT to systemic treatment was associated with a significantly better OS (p = 0.020) and PFS (p = 0.041) than systemic therapy alone. The incremental cost-effectiveness ratio (ICER) value indicated an average cost of €3792 for each month of survival after STRT and confirmed clinical effectiveness but higher healthcare costs. This real-world study suggests that upfront aRT in this setting represents a valid treatment strategy, boosting the efficacy of emerging drug classes with sustainable costs for the health service. Aim: Healthcare administrative databases represent a valuable source for real-life data analysis. The primary aim of this study is to compare effectiveness and cost profile in non-small-cell lung cancer (NSCLC) patients harboring synchronous brain metastases (BMs) who received non-chemo first-line systemic therapy with or without advanced radiotherapy (aRT). Methods: Diagnostic ICD-9-CM codes were used for identifying all patients with a new diagnosis of lung cancer between 2012 and 2019. Among these, patients who had started a first-line systemic treatment with either TKIs or pembrolizumab, alone or in combination with intensity-modulated or stereotactic RT, were selected. Clinical outcomes investigated included overall survival (OS), progression-free survival (PFS), and time-to-treatment failure (TTF). The cost outcome was defined as the average per capita cumulative healthcare direct costs of the treatment, including all inpatient and outpatient costs. Results: The final cohort included 177 patients, of whom 58 were treated with systemic treatment plus aRT (STRT) and 119 with systemic treatment alone. The addition of aRT to systemic treatment was associated with a significantly better OS (p = 0.020) and PFS (p = 0.041) than systemic therapy alone. The ICER (incremental cost-effectiveness ratio) value indicated an average cost of €3792 for each month of survival after STRT treatment and confirmed clinical effectiveness but higher healthcare costs. Conclusions: This real-world study suggests that upfront aRT for NCLSC patients with synchronous BMs represents a valid treatment strategy, boosting the efficacy of novel and emerging drug classes with sustainable costs for the health service. Translational relevance: The present real-world study reports that the use of upfront advanced radiotherapyaRT and new-generation systemic agents, such as TKIs and pembrolizumab, may have higher oncological control and an improved cost-effectiveness profile than the use of new-generation systemic agents alone in NCLSC patients with synchronous brain metastases. Acquired evidence can also be used to inform policymakers that adding advanced radiotherapy results is a sustainable cost for the health service. Since approximately 50% of patients do not meet RCT inclusion criteria, a significant proportion of them is receiving treatment that is not evidence-informed; therefore, these results warrant further studies to identify the best radiotherapy timing and possible dose escalation approaches to improving treatment efficacy in patient subgroups not typically represented in randomized controlled trials. [ABSTRACT FROM AUTHOR]

Background: It was previously reported that the production of exerkines is positively associated with the beneficial effects of exercise in lung adenocarcinoma (LUAD) patients. This study proposes a novel scoring system based on muscle failure-related genes, to assist in clinical decision making. Methods: A comprehensive analysis of bulk and single cell RNA sequencing (scRNA-seq) of early, advanced and brain metastatic LUAD tissues and normal lung tissues was performed to identify muscle failure-related genes in LUAD and to determine the distribution of muscle failure-related genes in different cell populations. A novel scoring system, named MFI (Muscle failure index), was developed and validated. The differences in biological functions, immune infiltration, genomic alterations, and clinical significance of different subtypes were also investigated. Results: First, we conducted single cell analysis on the dataset GSE131907 and identified eight cell subpopulations. We found that four muscle failure-related genes (BDNF, FNDC5, IL15, MSTN) were significantly increased in tumor cells. In addition, IL15 was widely distributed in the immune cell population. And we have validated it in our own clinical cohort. Then we created the MFI model based on 10 muscle failure-related genes using the LASSO algorithm, and MFI remained an independent prognostic factor of OS in both the training and validation cohorts. Moreover, we generated MFI in the single-cell dataset, in which cells with high MFI received and sent more signals compared to those with low MFI. Biological function analysis of both subtypes revealed stronger anti-tumor immune activity in the low MFI group, while tumor cells with high MFI had stronger metabolic and proliferative activity. Finally, we systematically assessed the immune cell activity and immunotherapy responses in LUAD patients, finding that the low MFI group was more sensitive to immunotherapy. Conclusion: Overall, our study can improve the understanding of the role of muscle failure-related genes in tumorigenesis and we constructed a reliable MFI model for predicting prognosis and guiding future clinical decision making. [ABSTRACT FROM AUTHOR]

Recent advances in treating cutaneous melanoma have resulted in impressive patient survival gains. Refinement of disease staging and accurate patient risk classification have significantly improved our prognostic knowledge and ability to accurately stratify treatment. Undoubtedly, the most important step towards optimizing patient outcomes has been the advent of cancer immunotherapy, in the form of immune checkpoint inhibition (ICI). Immunotherapy has established its cardinal role in the management of both early and late-stage melanoma. Through leveraging outcomes in melanoma, immunotherapy has also extended its benefit to other types of skin cancers. In this review, we endeavor to summarize the current role of immunotherapy in melanoma and non-melanoma skin cancers, highlight the most pertinent immunotherapy-related molecular biomarkers, and lastly, shed light on future research directions. [ABSTRACT FROM AUTHOR]

Background: PD-1/PD-L1 inhibitors are approved treatments for patients with esophageal squamous cell carcinoma (ESCC). The present investigation aspired to explore the interrelation between molecular phenotype and PD-L1 expression in ESCC. Methods: PD-L1 testing and targeted next-generation sequencing (NGS) were performed on tumoral tissues from 139 ESCC patients. Tumor-infiltrating lymphocytes (TILs) were scrutinized using a tyramide signal amplification system combined with immunohistochemistry. Results: Among enrolled patients, 36.7% displayed high PD-L1 expression (combined positive score [CPS] ≥10). BRCA1 and NF1 gene mutations were significantly associated with high PD-L1 expression (p < .05) while TGFβ pathway alterations were linked to low PD-L1 expression (p = .02). High copy number instability (CNI) and copy number alterations (CNA) were correlated with low PD-L1 expression. Patients with CDKN2A deletion exhibited higher PD-L1 expression. Varying types of TILs were observed across different PD-L1 expression groups. The ratio of CD8+PD-L1+ T cells and CD8+PD-1+ T cells to CD8+ T cells remained comparable in both tumoral and stromal regions, but the ratio of CD68+PD-L1+ macrophages to CD68+ macrophages was higher than the ratio of CD68+PD-1+ macrophages to CD68+ macrophages. CPS was significantly correlated with PD-L1+ lymphocytes and CD68+ macrophages in the tumoral region. CD8+ T cell infiltration was positively correlated with PD-1+ cells in both tumoral and stromal regions. Conclusion: In this study, we presented the prevalence rates of PD-L1 expression in Chinese ESCC patients. The association of genetic profiles with PD-L1 expression levels also provide the clue that genomic phenotype may interact with the immunologic phenotype in ESCC. [ABSTRACT FROM AUTHOR]

Despite the recent successes and durable responses with immune checkpoint inhibitors (ICI), many cancer patients, including those with melanoma, do not derive long-term benefits from ICI therapies. The lack of predictive biomarkers to stratify patients to targeted treatments has been the driver of primary treatment failure and represents an unmet medical need in melanoma and other cancers. Understanding genomic correlations with response and resistance to ICI will enhance cancer patients' benefits. Building on insights into interplay with the complex tumor microenvironment (TME), the ultimate goal should be assessing how the tumor 'instructs' the local immune system to create its privileged niche with a focus on genomic reprogramming within the TME. It is hypothesized that this genomic reprogramming determines the response to ICI. Furthermore, emerging genomic signatures of ICI response, including those related to neoantigens, antigen presentation, DNA repair, and oncogenic pathways, are gaining momentum. In addition, emerging data suggest a role for checkpoint regulators, T cell functionality, chromatin modifiers, and copy-number alterations in mediating the selective response to ICI. As such, efforts to contextualize genomic correlations with response into a more insightful understanding of tumor immune biology will help the development of novel biomarkers and therapeutic strategies to overcome ICI resistance. [ABSTRACT FROM AUTHOR]

Background: Immune interactions play important roles in the regulation of T cells' cytotoxic function, further impacting the anti-tumor efficacy of immunotherapy. A comprehensive analysis of immune cell types in HCC and immune-cell-related signatures predicting prognosis and monitoring immunotherapy efficacy is still absent. Methods: More than 1,300 hepatocellular carcinomas (HCC) patients were collected from public databases and included in the present study. The ssGSEA algorithm was applied to calculate the infiltration level of 28 immunocyte subpopulations. A cell pair algorithm was applied to construct an immune-cell-related prognostic index (ICRPI). Survival analyses were performed to measure the survival difference across ICRPI risk groups. Spearman's correlation analyses were used for the relevance assessment. A Wilcoxon test was used to measure the expression level's differences. Results: In this study, 28 immune subpopulations were retrieved, and 374 immune cell pairs (ICPs) were established, 38 of which were picked out by the least absolute shrinkage and selection operator (LASSO) algorithm. By using the selected ICPs, the ICRPI was constructed and validated to play crucial roles in survival stratification and dynamic monitoring of immunotherapy effect. We also explored several candidate drugs targeting ICRPI. A composite ICRPI and clinical prognostic index (ICPI) was then constructed, which achieved a more accurate estimation of HCC's survival and is a better choice for prognosis predictions in HCC. Conclusions: In conclusion, we constructed and validated ICRPI based on the cell pair algorithm in this study, which might provide some novel insights for increasing the survival estimation and clinical response to immune therapy for individual HCC patients and contribute to the personalized precision immunotherapy strategy of HCC. [ABSTRACT FROM AUTHOR]

Simple Summary: Short, dysfunctional telomeres represent the genetic biomarkers of cancer. Studies in early-stage non-small-cell lung cancer (NSCLC) have shown that telomere length and telomerase levels are correlated with survival. In patients with advanced NSCLC, telomere status has not yet been investigated, and its clinical significance remains unknown. We studied telomere length and the expression of telomerase and shelterin genes in a cohort of 79 patients with advanced NSCLC, and evaluated these parameters as potential prognostic and predictive factors. Telomere shortening, high levels of telomerase and aberrant expression of shelterin genes TRF2, RAP1 and TIN2 were significantly correlated with shorter survival. Furthermore, a worse response to immunotherapy was observed in patients with shorter telomeres. The determination of telomere parameters in advanced NSCLC could be useful for individualized treatment decisions. Telomere length appears to correlate with survival in early non-small-cell lung cancer (NSCLC), but the prognostic impact of telomere status in advanced NSCLC remains undetermined. Our purpose was to evaluate telomere parameters as prognostic and predictive biomarkers in advanced NSCLC. In 79 biopsies obtained before treatment, we analyzed the telomere length and expression of TERT and shelterin complex genes (TRF1, TRF2, POT1, TPP1, RAP1, and TIN2), using quantitative PCR. Non-responders to first-line chemotherapy were characterized by shorter telomeres and low RAP1 expression (p = 0.0035 and p = 0.0069), and tended to show higher TERT levels (p = 0.058). In multivariate analysis, short telomeres were associated with reduced event-free (EFS, p = 0.0023) and overall survival (OS, p = 0.00041). TERT and TRF2 overexpression correlated with poor EFS (p = 0.0069 and p = 0.00041) and OS (p = 0.0051 and p = 0.007). Low RAP1 and TIN2 expression-levels were linked to reduced EFS (p = 0.00032 and p = 0.0069) and OS (p = 0.000051 and p = 0.02). Short telomeres were also associated with decreased survival after nivolumab therapy (p = 0.097). Evaluation of telomere status in advanced NSCLC emerges as a useful biomarker that allows for the selection of patient groups with different clinical evolutions, to establish personalized treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: Hepatocellular carcinoma (HCC) is among the most common cancers and causes about 830,000 deaths annually in the world. Metabolic reprogramming is a critical hallmark of HCC, enabling HCC cells to adapt to the high energy demands necessary for fast growth. However, the clinical relevance of metabolic alteration in HCC has not been systematically assessed. By performing cross-species comparison of genomic data from mouse and human tissues, we identified three distinct metabolic subtypes of HCC and uncovered clinical and molecular characteristics associated with three subtypes. Importantly, we showed that the high metabolic subtype is less susceptible to immunotherapy and uncovered a potential mechanism associated with resistance to immunotherapy. High metabolic activity is a hallmark of cancers, including hepatocellular carcinoma (HCC). However, the molecular features of HCC with high metabolic activity contributing to clinical outcomes and the therapeutic implications of these characteristics are poorly understood. We aimed to define the features of HCC with high metabolic activity and uncover its association with response to current therapies. By integrating gene expression data from mouse liver tissues and tumor tissues from HCC patients (n = 1038), we uncovered three metabolically distinct HCC subtypes that differ in clinical outcomes and underlying molecular biology. The high metabolic subtype is characterized by poor survival, the strongest stem cell signature, high genomic instability, activation of EPCAM and SALL4, and low potential for benefitting from immunotherapy. Interestingly, immune cell analysis showed that regulatory T cells (Tregs) are highly enriched in high metabolic HCC tumors, suggesting that high metabolic activity of cancer cells may trigger activation or infiltration of Tregs, leading to cancer cells' evasion of anti-cancer immune cells. In summary, we identified clinically and metabolically distinct subtypes of HCC, potential biomarkers associated with these subtypes, and a potential mechanism of metabolism-mediated immune evasion by HCC cells. [ABSTRACT FROM AUTHOR]

Background: The expression of INMT (indolethylamine N-methyltransferase) has been reported to be downregulated in non-small-cell lung cancer (NSCLC). However, the role of INMT in NSCLC remains elusive. We aim to investigate the underlying mechanisms and clinical value of INMT in NSCLC, especially in lung adenocarcinoma (LUAD). Methods: Gene expression cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed to assess the effect of INMT on NSCLC. Gene expression data from an immunotherapy cohort were used to investigate the association of INMT with immunotherapy in NSCLC. Results: INMT expression was significantly downregulated in NSCLC compared with adjacent normal tissues. Downregulated INMT was associated with poor overall survival in LUAD, but not in lung squamous carcinoma. Multivariate Cox regression analysis suggested that INMT was an independent prognostic marker in LUAD. INMT had a reference value in the diagnosis and prognostic estimation of LUAD. Gene set enrichment analysis showed that pathways of the cell cycle and DNA damage response were enriched in the INMT low-expression group. The top 10 hub genes upregulated in the INMT low-expression group mainly activated the cell cycle pathway. In addition, more frequently mutated TP53 genes, higher aneuploidy scores, a fraction of genomes altered, MANTIS scores, and tumor mutation burden were found in tumors with low expression of INMT. Furthermore, patients with low expression of INMT showed favorable clinical benefits to anti-PD-1 treatment with higher enrichment scores of immune-related signatures. Conclusion: The low expression of INMT was associated with poor prognosis but favorable immunotherapy response in LUAD. INMT may affect the progression of LUAD by regulating the cell cycle and may serve as a valuable independent prognostic biomarker in patients with LUAD. [ABSTRACT FROM AUTHOR]

Metastatic melanoma is a highly immunogenic tumor with very poor survival rates due to immune system escape-mechanisms. Immune checkpoint inhibitors (ICIs) targeting the cytotoxic T-lymphocyte-associated protein 4 (CTLA4) and the programmed death-1 (PD1) receptors, are being used to impede immune evasion. This immunotherapy entails an increment in the overall survival rates. However, melanoma cells respond with evasive molecular mechanisms. ERK cascade inhibitors are also used in metastatic melanoma treatment, with the RAF activity blockade being the main therapeutic approach for such purpose, and in combination with MEK inhibitors improves many parameters of clinical efficacy. Despite their efficacy in inhibiting ERK signaling, the rewiring of the melanoma cell-signaling results in disease relapse, constituting the reinstatement of ERK activation, which is a common cause of some resistance mechanisms. Recent studies revealed that the combination of RAS–ERK pathway inhibitors and ICI therapy present promising advantages for metastatic melanoma treatment. Here, we present a recompilation of the combined therapies clinically evaluated in patients. [ABSTRACT FROM AUTHOR]

Simple Summary: In the past few decades, targeted therapy and immunotherapy have transformed tremendously the chances of survival. Checkpoint inhibitors that block programmed cell death 1 (PD-1) and cytotoxic T-lymphocyte antigen 4 (CTLA-4) pathways hold the most promise. However, more than half of the patients treated with CTLA-4-PD1 inhibition suffered from grade 3 or 4 treatment-related adverse events (TRAEs). Recently, Tawbi et al. reported the initial results of the phase 2–3 RELATIVITY-047 trial which evaluated LAG3-PD1 inhibition of relatlimab plus nivolumab in patients with previously untreated advanced melanoma. Here, we performed an indirect cross-comparison of LAG3-PD1 and CTLA4-PD1 inhibition in patients with previously untreated advanced melanoma by deriving individual patient survival data and safety profiles. We found that the PFS of LAG3-PD1 and CTLA4-PD1 inhibition were similar. Compared with CTLA4-PD1-inhibition, LAG3-PD1 inhibition tended to exhibit earlier survival benefit and lesser TRAEs. Objective: To compare the inhibition of LAG3-PD1 versus the inhibition of CTLA-4-PD1 in patients with previously untreated advanced melanoma. Methods: The individual participant data (IPD) were extracted from the KM plots using a graphical reconstructive algorithm. Log-rank, Cox proportional hazard model, Bayesian hierarchical model with time-varying hazard ratio (HR) effect, and restricted mean survival time (RMST) were performed to estimate survival benefits. Results: The CheckMate-067 (n = 630) and RELATIVITY-047 (n = 714) trials were included for analysis. The graphical reconstructive algorithm showed that IPD had similar HRs and log-rank values as the original plots. The HR of nivolumab plus relatlimab (LAG3 inhibitor) versus nivolumab plus ipilimumab (CTLA4 inhibitor) was 1.19 (95% confidence interval [CI] 0.96 to1.48). The 24-months RMST of nivolumab plus relatlimab versus nivolumab was 2.35 (95% CI 0.77–3.94) months, compared with 1.87 (95% CI, 0.25–3.49) months for nivolumab plus ipilimumab versus nivolumab. The Bayesian hierarchical model showed that patients treated with nivolumab plus relatlimab had earlier PFS benefits than those with nivolumab plus ipilimumab. Grade 3 or 4 treatment-related adverse events occurred in 18.9% of patients using nivolumab plus relatlimab and 55.0% of patients using nivolumab plus ipilimumab. Conclusions: These findings suggest that the PFS of LAG3-PD1 and CTLA4-PD1 inhibition were similar and LAG3-PD1 inhibition exhibited earlier survival benefit and lesser TRAEs. [ABSTRACT FROM AUTHOR]

Tumor immunotherapy is considered as one of the most promising methods in cancer treatment in recent years. Immune checkpoint blockade (ICB) can activate immune cells to destroy tumors by relieving the inhibitory pathway of tumor cells to immune cells. In silico prediction of the ICB response is an important step toward achieving effective and personalized cancer immunotherapy. Although immune checkpoint inhibitors have shown exciting clinical effects in the treatment of many types of tumors, there are still some clinical problems in practical application, such as low response rate and large individualized differences. How to predict the efficacy of effective individualized immune checkpoint inhibitors for tumor patients based on specific biomarkers and computational models is one of the key issues in the immunotherapy of this kind of tumor. In our work, from the five levels of genome level, transcription level, epigenetic level, microbial taxonomy level, and the immune cell infiltration profile level, the biomarkers and in silico calculation methods that affect the efficacy of tumor immune checkpoint inhibitors are comprehensively summarized. [ABSTRACT FROM AUTHOR]

Although immune checkpoint blockade (ICB) therapies have achieved great progress, the patient response varies among cancers. In this study, we analyzed the potential genomic indicators contributing to ICB therapy response. The results showed that high tumor mutation burden (TMB) failed to predict response in anti-PD1 treated melanoma. SERPINB3 was the most significant response-related gene in melanoma and mutations in either SERPINB3 or PEG3 can serve as an independent risk factor in melanoma. Some recurrent mutations in CSMD3 were only in responders or non-responders, indicating their diverse impacts on patient response. Enrichment scores (ES) of gene mutations in 12 biological pathways were significantly higher in responders or non-responders. Next, the P-TMB calculated from genes in these pathways was significantly related to patient response with prediction AUC 0.74–0.82 in all collected datasets. In conclusion, our work provides new insights into the application of TMB in predicting patient response, which will benefit to immunotherapy research. [ABSTRACT FROM AUTHOR]