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Background: Adolescents and young adults frequently receive chemotherapy near death. We know less about the use of targeted agents and immunotherapy or trends over time., Methods: We conducted a retrospective cohort study of 1836 adolescents and young adults with cancer who died between 2009 and 2019 after receiving care at 1 of 3 sites (Dana-Farber Cancer Institute, Kaiser Permanente Northern California, and Kaiser Permanente Southern California). We reviewed electronic health data and medical records to examine use of cancer-directed therapy in the last 90 days of life, including chemotherapy, targeted therapy, immunotherapy, and investigational drugs., Results: Over the study period, 35% of adolescents and young adults received chemotherapy in the last 90 days of life; 24% received targeted therapy, 7% immunotherapy, and 5% investigational drugs. Additionally, 56% received at least 1 form of systemic cancer-directed therapy in the last 90 days of life. After adjustment for patient sex, race, ethnicity, age, site of care, diagnosis, and years from diagnosis to death, the proportion of adolescents and young adults receiving targeted therapy (odds ratio [OR] = 1.05 per year of death, 95% confidence interval [CI] = 1.02 to 1.10; P = .006), immunotherapy (OR = 1.27, 95% CI = 1.18 to 1.38; P < .0001), and any cancer-directed therapy (OR = 1.04, 95% CI = 1.01 to 1.08; P = .01) in the last 90 days of life increased over time., Conclusions: More than half of adolescents and young adults receive cancer therapy in the last 90 days of life, and use of novel agents such as targeted therapy and immunotherapy is increasing over time. Although some adolescents and young adults may wish to continue cancer therapy while living with advanced disease, efforts are needed to ensure that use of cancer-directed therapy meets preferences of adolescents and young adults approaching death., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

The pattern of the difference between two survival curves we often observe in randomized clinical trials for evaluating immunotherapy is not proportional hazards; the treatment effect typically appears several months after the initiation of the treatment (ie, delayed difference pattern). The commonly used logrank test and hazard ratio estimation approach will be suboptimal concerning testing and estimation for those trials. The long-term restricted mean survival time (LT-RMST) approach is a promising alternative for detecting the treatment effect that potentially appears later in the study. A challenge in employing the LT-RMST approach is that it must specify a lower end of the time window in addition to a truncation time point that the RMST requires. There are several investigations and suggestions regarding the choice of the truncation time point for the RMST. However, little has been investigated to address the choice of the lower end of the time window. In this paper, we propose a flexible LT-RMST-based test/estimation approach that does not require users to specify a lower end of the time window. Numerical studies demonstrated that the potential power loss by adopting this flexibility was minimal, compared to the standard LT-RMST approach using a prespecified lower end of the time window. The proposed method is flexible and can offer higher power than the RMST-based approach when the delayed treatment effect is expected. Also, it provides a robust estimate of the magnitude of the treatment effect and its confidence interval that corresponds to the test result., (© 2023 John Wiley & Sons Ltd.)

The hazard ratio (HR) has been the most popular measure to quantify the magnitude of treatment effect on time-to-event outcomes in clinical research. However, the traditional Cox's HR approach has several drawbacks. One major issue is that there is no clear interpretation when the proportional hazards (PH) assumption does not hold, because the estimated HR is affected by study-specific censoring time distribution in non-PH cases. Another major issue is that the lack of a group-specific absolute hazard value in each group obscures the clinical significance of the magnitude of the treatment effect. Given these, we propose average hazard with survival weight (AH-SW) as a summary metric of event time distribution and will use difference in AH-SW (DAH-SW) or ratio of AH-SW (RAH-SW) to quantify the treatment effect magnitude. The AH-SW is interpreted as a person-time incidence rate that does not depend on random censoring. It is defined as the ratio of cumulative incidence probability and restricted mean survival time (RMST), which can be estimated non-parametrically. Numerical studies demonstrate that DAH-SW and RAH-SW offer almost identical power to Cox's HR-based tests under PH scenarios and can be more powerful for delayed-difference patterns often seen in immunotherapy trials. Like median and RMST differences, the proposed approach is a good model-free alternative to the HR-based approach for evaluating the treatment effect magnitude. Such a model-free measure will increase the likelihood that results from clinical studies are correctly interpreted and generalized to future populations., (© 2023 John Wiley & Sons Ltd.)

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.)

Cancer is a disease that mostly affects older adults and because of the aging of the population, the number of older adults diagnosed with cancer will increase significantly around the world. With increasing age, more older adults are living with frailty, and this may impact the tolerability of cancer treatments. International guidelines, such as the American Society for Clinical Oncology geriatric oncology guideline, recommend a geriatric assessment and management for all older adults with cancer to support the treatment decision-making process as well as develop a plan for supportive care interventions to support the older adults during cancer treatments. While there is clinical trial evidence to support a geriatric assessment and management for older adults receiving chemotherapy, there is less evidence to support a geriatric assessment for older adults starting immunotherapy. There are increasing numbers of new immunotherapies and targeted therapies available for older adults with cancer but often few older adults have been included in the clinical trials, leaving less evidence for clinicians to guide treatment decisions. In this current opinion, we review the current evidence on the use of a geriatric assessment and management in the context of immunotherapy and targeted therapy. We review how a geriatric assessment could support older adults making treatment decisions for immunotherapy, review how geriatric assessment parameters are linked with outcomes and provide guidance on how geriatric assessment can guide the supportive care plan during immunotherapy treatment., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Importance: In a comparative clinical study with progression-free survival (PFS) or overall survival (OS) as the end point, the hazard ratio (HR) is routinely used to design the study and to estimate the treatment effect at the end of the study. The clinical interpretation of the HR may not be straightforward, especially when the underlying model assumption is not valid. A robust procedure for study design and analysis that enables clinically meaningful interpretation of trial results is warranted., Objective: To discuss issues of conventional trial design and analysis and to present alternatives to the HR using a recent immunotherapy study as an illustrative example., Design, Setting, and Participants: By comparing 2 groups in a survival analysis, we discuss issues of using the HR and present the restricted mean survival time (RMST) as a summary measure of patients’ survival profile over time. We show how to use the difference or ratio in RMST between 2 groups as an alternative for designing and analyzing a clinical study with an immunotherapy study as an illustrative example., Main Outcomes and Measures: Overall survival or PFS. Group contrast measures included HR, RMST difference or ratio, and the event rate difference., Results: For the illustrative example, the HR procedure indicates that nivolumab significantly prolonged patient OS and was numerically better than docetaxel for PFS. However, the median PFS time of docetaxel was significantly better than that of nivolumab. Therefore, it may be difficult to use median OS and/or PFS to interpret of the HR value clinically. On the other hand, using RMST difference, nivolumab was significantly better than docetaxel for both OS and PFS. We also provide details regarding design of a future study with RMST-based measures., Conclusions and Relevance: The design and analysis of a conventional cancer clinical trial can be improved by adopting a robust statistical procedure that enables clinically meaningful interpretations of the treatment effect. The RMST-based quantitative method may be used as a primary tool for future cancer trials or to help us to better understand the clinical interpretation of the HR even when its model assumption is plausible.

Thus far immunotherapy has had limited impact on ovarian cancer. Vigil (a novel DNA-based multifunctional immune-therapeutic) has shown clinical benefit to prolong relapse-free survival (RFS) and overall survival (OS) in the BRCA wild type and HRP populations. We further analyzed molecular signals related to sensitivity of Vigil treatment. Tissue from patients enrolled in the randomized double-blind trial of Vigil vs. placebo as maintenance in frontline management of advanced resectable ovarian cancer underwent DNA polymorphism analysis. Data was generated from a 981 gene panel to determine the tumor mutation burden and classify variants using Ingenuity Variant Analysis software (Qiagen) or NIH ClinVar. Only variants classified as pathogenic or likely pathogenic were included. STRING application (version 1.5.1) was used to create a protein-protein interaction network. Topological distance and probability of co-mutation were used to calculated the C-score and cumulative C-score (cumC-score). Kaplan-Meier analysis was used to determine the relationship between gene pairs with a high cumC-score and clinical parameters. Improved relapse free survival in Vigil treated patients was found for the TP53m-BRCAwt-HRP group compared to placebo (21.1 months versus 5.6 months p = 0.0013). Analysis of tumor mutation burden did not reveal statistical benefit in patients receiving Vigil versus placebo. Results suggest a subset of ovarian cancer patients with enhanced susceptibility to Vigil immunotherapy. The hypothesis-generating data presented invites a validation study of Vigil in target identified populations, and supports clinical consideration of STRING-generated network application to biomarker characterization with other cancer patients targeted with Vigil., (© 2021. The Author(s).)

Nonproportional hazards (NPHs) are often observed in survival trials such as the immunotherapy cancer trials. Under NPH, the classical log-rank test can be inefficient, and the estimated hazards ratio from the Cox model is difficult to interpret. The weighted log-rank test, and the tests for comparing the restricted mean survival time or the milestone survival become increasingly popular in handling NPH. The sample size calculation for these tests may require high-dimensional numerical integration. We present a sample size determination method for survival trials via product integration on the basis of a continuous-time multistate Markov model. The main challenge of the method lies in the design of the multistate model under a complex NPH pattern, and this is illustrated for NPH induced by delayed effect with individual heterogeneity in the lag duration, cure fractions, and treatment switching due to disease progression or noncompliance. Numerical examples are presented to demonstrate the accuracy of the proposed method. We obtain the following findings. The powers of the tests for milestone survival and RMST depend on both the trial duration and milestone timepoint, and may not increase as the milestone timepoint increases. If the milestone timepoint is appropriately chosen, the RMST test can be more powerful than the conventional log-rank test in the presence of diminishing treatment effect or in the proportional hazards cure model. In general, the RMST test yields lower power than a proper Fleming-Harrington weighted log-rank test., (© 2021 John Wiley & Sons Ltd.)

Immunotherapy has revolutionized cancer treatment and substantially improved patient outcome with regard to multiple tumour types. However, most patients still do not benefit from such therapies, notably because of the absence of pre-existing T cell infiltration. DNA damage response (DDR) deficiency has recently emerged as an important determinant of tumour immunogenicity. A growing body of evidence now supports the concept that DDR-targeted therapies can increase the antitumour immune response by (1) promoting antigenicity through increased mutability and genomic instability, (2) enhancing adjuvanticity through the activation of cytosolic immunity and immunogenic cell death and (3) favouring reactogenicity through the modulation of factors that control the tumour-immune cell synapse. In this Review, we discuss the interplay between the DDR and anticancer immunity and highlight how this dynamic interaction contributes to shaping tumour immunogenicity. We also review the most innovative preclinical approaches that could be used to investigate such effects, including recently developed ex vivo systems. Finally, we highlight the therapeutic opportunities presented by the exploitation of the DDR-anticancer immunity interplay, with a focus on those in early-phase clinical development., (© 2021. Springer Nature Limited.)

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 cell infiltration is important for predicting the clinical outcomes of colorectal cancer. Integrin β7 (ITGB7), which is expressed on the surface of leukocytes, plays an essential role in the homing of immune cells to gut-associated lymphoid tissue and facilitating the retention of lymphocytes in gut epithelium; however, its role in colorectal cancer pathogenesis is poorly explored. Here, we found that the number of β7 + cells decreased significantly in tumor tissue compared with adjacent normal tissue. β7 expression decreased in tumor-derived compared with normal tissue-derived CD8 + T cells. With bulk RNA expression data from public platforms, we demonstrated that higher ITGB7 expression correlated with longer patient survival, higher cytotoxic immune cell infiltration, lower somatic copy-number alterations, decreased mutation frequency of APC and TP53 , and better response to immunotherapy. The possible cell-cell interactions mediated by ITGB7 and its ligands MAdCAM-1, VCAM-1, and CDH1 were investigated using public single-cell RNA sequencing data. ITGB7 deficiency led to exaggerated tumorigenesis and progression in both Apc min /+ spontaneous and MC38 orthotopic models of colorectal cancer, which could be due to a reduced infiltration of activated CD8 + T cells, effector memory CD8 + T cells, IFNγ + CD8 + T cells, IFNγ + natural killer cells, CD103 + dendritic cells, and other immune cell subsets that are essential players in antitumor immunity. In conclusion, our data revealed that ITGB7 could inhibit the tumorigenesis and progression of colorectal cancer by maintaining antitumor immunity., (©2021 American Association for Cancer Research.)

Most statistical tests for treatment effects used in randomized clinical trials with survival outcomes are based on the proportional hazards assumption, which often fails in practice. Data from early exploratory studies may provide evidence of nonproportional hazards, which can guide the choice of alternative tests in the design of practice-changing confirmatory trials. We developed a test to detect treatment effects in a late-stage trial, which accounts for the deviations from proportional hazards suggested by early-stage data. Conditional on early-stage data, among all tests that control the frequentist Type I error rate at a fixed α level, our testing procedure maximizes the Bayesian predictive probability that the study will demonstrate the efficacy of the experimental treatment. Hence, the proposed test provides a useful benchmark for other tests commonly used in the presence of nonproportional hazards, for example, weighted log-rank tests. We illustrate this approach in simulations based on data from a published cancer immunotherapy phase III trial., (© 2020 The International Biometric Society.)

Immune checkpoint inhibition (ICI) has revolutionized cancer treatment, and produced durable responses in many cancer types. However, there remains a subset of patients that do not respond despite their tumors exhibiting PD-L1 expression, which highlights the need for additional biomarkers relevant to response. Here, we review checkpoint inhibitor signal pathways, resistance and sensitivity mechanisms, as well as response rates. We also investigate the correlation and response to ICI with BRCA1/2 mutation status and homologous recombination deficient tumors. Collectively we show that the use of tumor mutational burden may be effective as an emerging biomarker.

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.

Background: Body mass index (BMI) is used to define obesity, but it is an imperfect measure of body composition. In the current study, the authors explored the association between types of fat and survival in patients treated with immunotherapy., Methods: A retrospective analysis of 90 patients who were treated with immunotherapy on phase 1 clinical trials at the Winship Cancer Institute in Atlanta, Georgia, from 2009 through 2017 was performed. Overall survival (OS) and progression-free survival (PFS) were used to measure clinical outcomes. Baseline BMI and radiographic images at the middle of the third lumbar vertebrae were obtained. Fat densities were calculated and converted to indices (subcutaneous fat index [SFI], intermuscular fat index [IFI], and visceral fat index [VFI]) after dividing by height in meters squared. Risk groups were created using recursive partitioning and the regression trees method for SFI and IFI, which were selected by stepwise variable selection among all fat-related variables. The Cox proportional hazards model and Kaplan-Meier method were used for the association with OS and PFS., Results: The majority of patients (59%) were male and diagnosed with melanoma (33%) or gastrointestinal cancers (22%). The median BMI was 27.4 kg/m 2 , the median SFI was 62.78, the median IFI was 4.06, and the median VFI was 40.53. Low-risk patients (those with an SFI ≥73) had a significantly longer OS (hazard ratio, 0.20; 95% CI, 0.09-0.46 [P < .001]) and PFS (hazard ratio, 0.38; 95% CI, 0.20-0.72 [P = .003]) compared with patients at intermediate risk (those with an SFI <73 and IFI <3.4) and poor risk (those with an SFI <73 and IFI ≥3.4). The Uno concordance statistics were found to be higher for fat risk groups than BMI in predicting OS (0.603 vs 0.574; P = .581) and PFS (0.602 vs 0.586; P = .71)., Conclusions: Increased BMI, increased SFI, and decreased IFI may be associated with prolonged survival in patients with cancer who are treated with immunotherapy. Further studies are needed to elucidate the effect of adiposity on the host immune response to immunotherapy., (© 2019 American Cancer Society.)

Anticancer immunotherapies involving the use of immune-checkpoint inhibitors or adoptive cellular transfer have emerged as new therapeutic pillars within oncology. These treatments function by overcoming or relieving tumour-induced immunosuppression, thereby enabling immune-mediated tumour clearance. While often more effective and better tolerated than traditional and targeted therapies, many patients have innate or acquired resistance to immunotherapies. Cancer immunoediting is the process whereby the immune system can both constrain and promote tumour development, which proceeds through three phases termed elimination, equilibrium and escape. Throughout these phases, tumour immunogenicity is edited, and immunosuppressive mechanisms that enable disease progression are acquired. The mechanisms of resistance to immunotherapy seem to broadly overlap with those used by cancers as they undergo immunoediting to evade detection by the immune system. In this Review, we discuss how a deeper understanding of the mechanisms underlying the cancer immunoediting process can provide insight into the development of resistance to immunotherapies and the strategies that can be used to overcome such resistance.

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]

Interactions between tumor cells and immune cells in the tumor microenvironment (TME) play a vital role the mechanisms of immune evasion, by which cancer cells escape immune elimination. Thus, the characterization and quantification of different components in the TME is a hot topic in molecular biology and drug discovery. Since the development of transcriptome sequencing in bulk tissue, single cells and spatial dimensions, there are increasing methods emerging to deconvolute and subtype the TME. This review discusses and compares such computational strategies and downstream subtyping analyses. Integrative analyses of the transcriptome with other data, such as epigenetics and T-cell receptor sequencing, are needed to obtain comprehensive knowledge of the dynamic TME. Executive summary Measuring the composition of tumor microenvironment Accurate measurement of the tumor microenvironment (TME) composition is essential to our understanding of the interplays between tumor cells and other cell types in the TME. In bulk-RNAseq analysis, canonical marker gene sets provide interpretable results; deconvolution strategies that use prior knowledge from scRNAseq have shown better overall performance. Probabilistic models in scRNAseq will play a pivot role in transcriptome analysis as cell subtype-specific gene distributions can be transferred to other computational analyses as prior knowledge. Current spatial transcriptome sequencing suffers from spot-based input; integration with scRNAseq contributes to more accurate and efficient deconvolution to single-cell resolution. Subtyping the TME Clustering the percentage of TME composition can subtype the microenvironment and bridge connections to the immune phenotype. Cell–cell networks based on similarity present the distance between cell subtypes in a certain network; cell–cell casual networks show potential downstream signals triggered by cell–cell communication. Future perspective Integrating transcriptome analysis with genomics, epigenetics, proteomics, T-cell receptor sequencing data and environmental factors has demonstrated that omics analysis will contribute to a more comprehensive understanding of the TME by adding more dimensions of information to the model. Tracking the dynamic cell–cell causal networks in the TME during treatment will help decipher the mechanisms of immune evasion. [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]

Background: The incidence of lung cancer tends to be younger, and adenocarcinoma is the main histological type. Even patients with the same tumor type may have significant differences in clinical features, tumor microenvironment and genomic background at different ages. Immune checkpoint inhibitors (ICIs) have been shown to improve clinical outcomes in patients with lung adenocarcinoma (LUAD). However, differences in ICI efficacy between older and younger patients are unknown. Our study aimed to explore the relationship between age and immunotherapy in LUAD. Methods: In our study, 1313 resected LUAD patients in our hospital were divided into young (age ≤ 50) and old groups (age > 50), and the clinical characteristic differences between them were analyzed. Of these, next-generation sequencing (NGS) was performed on the 311 cases. In addition, immune-related signatures of 508 LUAD patients were analyzed by TCGA RNA expression data. Then, we validated genomic and clinical information of 270 LUAD samples in the MSKCC cohort. Results: ERBB2 and EGFR gene mutations were significantly different between the two groups, and the gene mutation number in the old group was significantly higher than that in the young group. In addition, immune-related signatures of LUAD patients were analyzed by TCGA RNA expression data, which indicated that the patients in the old group might have a better immune microenvironment. Then, we validated the MSKCC cohort and found that the TMB of the old group was significantly higher than that of the young group, and the OS of immunotherapy was longer in the old group. Conclusion: Our study was the first to analyze the differences in the genomic landscape and immune-related biomarkers between the young and old groups of LUAD patients and found that the old group had a better efficacy of immunotherapy, providing a reference for the study design and treatment of patients with LUAD. [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]

Delayed separation of survival curves is a common occurrence in confirmatory studies in immuno‐oncology. Many novel statistical methods that aim to efficiently capture potential long‐term survival improvements have been proposed in recent years. However, the vast majority do not consider stratification, which is a major limitation considering that most large confirmatory studies currently employ a stratified primary analysis. In this article, we combine recently proposed weighted log‐rank tests that have been designed to work well under a delayed separation of survival curves, with stratification by a baseline variable. The aim is to increase the efficiency of the test when the stratifying variable is highly prognostic for survival. As there are many potential ways to combine the two techniques, we compare several possibilities in an extensive simulation study. We also apply the techniques retrospectively to two recent randomized clinical trials. [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]