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Purpose: Identifying cancer patients who are most at risk for venous thromboembolism (VTE) is essential to improve timely delivery of chemotherapy. Several studies have been performed to identify novel candidate biomarkers, but no agreement has yet been reached. In this light, we sought to analyze whether a dynamic evaluation of early changes of activated protein C (APC) function during chemotherapy could be predictive of a first VTE episode in cancer outpatients, thus improving risk stratification.Methods: A retrospective single-center pilot study was conducted to investigate the adequacy of a dynamic evaluation of a novel APC-dependent thrombin generation assay (HemosIL ThromboPath (ThP)) in predicting VTE in 208 ambulatory cancer patients, enrolled on the basis of tight inclusion criteria, prior to start and before the second cycle of a new chemotherapy regimen.Results: Retrospective analysis of samples showed the occurrence of an acquired APC resistance during chemotherapy, which was predictive of VTE. Univariate Cox proportional hazards survival analysis showed that early ThP changes predicted VTE (stable vs. decreasing ThP: hazard ratio (HR) 0.21; 95% CI 0.10-0.19; p < 0.0001), which was confirmed in the multivariate model (HR 0.25; CI 0.12-0.52, p < 0.0001). Stratification of patients according to a risk assessment model showed a 0.18 HR for stable vs. decreasing ThP assay results in an intermediate risk group.Conclusions: We may thus conclude that early changes of ThP assay in patients on active chemotherapy enhance VTE risk stratification, helping in identifying a population of cancer patients who might benefit from thromboprophylaxis. [ABSTRACT FROM AUTHOR]

Gangliosides are sialic acid-containing glycosphingolipids present in the outer leaflet of the plasma membrane of many cell types where they modulate adhesive processes. The main population of glycolipids in resting platelets is represented by ganglioside M3 (GM3). It has been demonstrated that following platelet activation ganglioside D3 (GD3) is rapidly formed from the GM3 pool. The present study was designed to evaluate the link between platelet activation and GD3 expression and to verify whether this ganglioside might play a role in modulating signal transduction events. Our results suggest that following platelet activation, GD3 is rapidly expressed on the platelet surface and internalised to the cytoskeleton where it transiently associates first with the Src family tyrosine kinase Lyn then with the Fc receptor γ chain. This sequence of events ultimately leads to an enhanced CD32 (the Fc receptor isoform present in platelets) expression on the platelet membrane. These data drive us to speculate that GD3 might act as second messenger in the activatory cascade, which leads to CD32 expression and triggers platelet adhesion and spreading to the subendothelial matrix. [Copyright &y& Elsevier]

Background: High expression of programmed death-ligand 1 (PD-L1) has been recognized as a marker of improved efficacy of immunotherapy in gastroesophageal adenocarcinoma (GEA); however, the optimal PD-L1 cut-off is still debated. The aim of the present review was to analyze available phase III trials and to identify the appropriate PD-L1 expression cut-off for GEA., Methods: Phase III trials investigating the efficacy of anti-programmed cell death protein 1 (PD-1) therapies in addition to standard chemotherapy versus standard chemotherapy in the first-line setting were selected. Progression-free survival (PFS), overall survival (OS) and objective response rate (ORR) were the analyzed outcome measures. Pooled treatment effects were assessed in the unselected population and in subpopulations with different levels of PD-L1 expression., Results: PD-1 blockade efficacy was found to consistently increase in a linear manner with higher combined positive score (CPS) of PD-L1 expression: pooled hazard ratio (HR) for OS and PFS and pooled odds ratio (OR) for ORR of 0.80, 0.75 and 1.51, respectively, in the unselected population versus 0.67, 0.63 and 1.90, respectively, in the CPS ≥10 population (all P values < 0.0001). In the PD-L1-negative population (CPS <1) a significant benefit of anti-PD-1 agents could not be demonstrated in terms of OS and PFS (P = 0.28 and 0.12, respectively), but it was seen in terms of ORR (P = 0.03). PD-1 blockade was effective in the CPS <10 population (P value for pooled OS HR, PFS HR and response OR are all 0.01), while in the CPS <5 population the effect was of borderline significance for OS (P = 0.07) and significant for PFS and ORR (P = 0.02 and 0.03, respectively)., Conclusion: The present meta-analysis confirmed that the benefit of PD-1 blockade in GEA patients is related to PD-L1 CPS, with increased benefit observed for higher CPS cut-offs and no OS benefit in the CPS <1 subset. Overall, data indicate that PD-L1 CPS ≥5 could represent an acceptable cut-off to optimize the risk/benefit ratio of such agents. Our data suggest a potential clinical benefit of immunotherapy in selected patients within the CPS 1-4 population which needs further investigation., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Machine learning models learn about general behavior from data by finding the relationships between features. Our purpose was to develop a predictive model to identify and predict which subset of colorectal cancer patients are more likely to experience chemotherapy-induced toxicity and to determine the specific attributes that influence the presence of treatment-related side effects., Methods: The predictor was general toxicity, and for the construction of our data training, we selected 95 characteristics that represent the health state of 74 patients prior to their first round of chemotherapy. After the data were processed, Random Forest models were trained to offer an optimal balance between accuracy and interpretability., Results: We constructed a machine learning predictor with an emphasis on assessing the importance of numerical and categorical variables in relation to toxicity., Conclusions: The incorporation of artificial intelligence in personalizing colorectal cancer management by anticipating and overseeing toxicities more effectively illustrates a pivotal shift towards more personalized and precise medical care.

The interplay between the immune system and chronic obstructive pulmonary disease (COPD) and non-small cell lung cancer (NSCLC) is complex and multifaceted. In COPD, chronic inflammation and oxidative stress can lead to immune dysfunction that can exacerbate lung damage, further worsening the respiratory symptoms. In NSCLC, immune cells can recognise and attack the cancer cells, which, however, can evade or suppress the immune response by various mechanisms, such as expressing immune checkpoint proteins or secreting immunosuppressive cytokines, thus creating an immunosuppressive tumour microenvironment that promotes cancer progression and metastasis. The interaction between COPD and NSCLC further complicates the immune response. In patients with both diseases, COPD can impair the immune response against cancer cells by reducing or suppressing the activity of immune cells, or altering their cytokine profile. Moreover, anti-cancer treatments can also affect the immune system and worsen COPD symptoms by causing lung inflammation and fibrosis. Immunotherapy itself can also cause immune-related adverse events that could worsen the respiratory symptoms in patients with COPD-compromised lungs. In the present review, we tried to understand the interplay between the two pathologies and how the efficacy of immunotherapy in NSCLC patients with COPD is affected in these patients.

(1) Background: Sarcopenia lasting >1 year might be considered a chronic condition in many HNSCC patients. CT-scan-derived Skeletal Muscle Mass Index (SMI) is an established surrogate of sarcopenia; yet, the cut-off reported in the literature (literature-based, lb-SMI < 43.2) is mainly based on the risk of chemoradiotherapy-induced toxicity, and the optimal value to discriminate OS is under-investigated. (2) Methods: The effect on OS of the lb-SMI cutoff was compared with an untailored OS-oriented SMI cutoff obtained in a cohort of consecutive advanced HNSCC patients treated with primary chemoradiotherapy, bio-chemotherapy or chemo-immunotherapy (cohort-specific, cs-SMI cutoff). Gender- and BMI-tailored (gt-SMI and bt-SMI) cut-offs were also evaluated. Cutoff values were identified by using the maximally selected rank statistics for OS. (3) Results: In 115 HNSCC patients, the cs-SMI cutoff was 31.50, which was lower compared to the lb-SMI reported cut-off. The optimal cut-off separately determined in females, males, overweight and non-overweight patients were 46.02, 34.37, 27.32 and 34.73, respectively. gt-SMI categorization had the highest effect on survival ( p < 0.0001); its prognostic value was independent of the treatment setting or the primary location and was retained in a multivariate cox-regression analysis for OS including other HNSCC-specific prognostic factors ( p = 0.0004). (4) Conclusions: A tailored SMI assessment would improve clinical management of sarcopenia in chemoradiotherapy-, bio-chemotherapy- or chemo-immunotherapy-treated HNSCC patients. Gender-based SMI could be used for prognostication in HNSCC patients.

Antibody-drug conjugates (ADCs) are complex chemical structures composed of a monoclonal antibody, serving as a link to target cells, which is conjugated with a potent cytotoxic drug (i.e., payload) through a chemical linker. Inspired by Paul Ehrlich's concept of the ideal anticancer drug as a "magic bullet", ADCs are also highly specific anticancer agents, as they have been demonstrated to recognize, bind, and neutralize cancer cells, limiting injuries to normal cells. ADCs are among the newest pharmacologic breakthroughs in treating solid and hematologic malignancies. Indeed, in recent years, various ADCs have been approved by the Food and Drug Administration and European Medicines Agency for the treatment of several cancers, resulting in a "practice-changing" approach. However, despite these successes, no ADC is approved for treating patients affected by renal cell carcinoma (RCC). In the present paper, we thoroughly reviewed the current literature and summarized preclinical studies and clinical trials that evaluated the activity and toxicity profile of ADCs in RCC patients. Moreover, we scrutinized the potential causes that, until now, hampered the therapeutical success of ADCs in those patients. Finally, we discussed novel strategies that would improve the development of ADCs and their efficacy in treating RCC patients.

Not all aspects of the disruption of iron homeostasis in cancer have been fully elucidated. Iron accumulation in cancer cells is frequent for many solid tumours, and this is often accompanied by the contemporary rise of two key iron regulators, HIF2α and Hepcidin. This scenario is different from what happens under physiological conditions, where Hepcidin parallels systemic iron concentrations while HIF2α levels are inversely associated to Hepcidin. The present review highlights the increasing body of evidence for the pro-tumoral effect of HIF2α and Hepcidin, discusses the possible imbalance in HIF2α, Hepcidin and iron homeostasis during cancer, and explores therapeutic options relying on these pathways as anticancer strategies., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: KRAS G12C -mutated metastatic colorectal cancer (mCRC) has recently been recognized as a distinct druggable molecular entity; however, there are limited data on its sensitivity to standard chemotherapy. In the near future, the combination of chemotherapy plus a KRAS G12C -inhibitor might become the standard of care; however, the optimal chemotherapy backbone is unknown., Methods: A multicentre retrospective analysis was conducted including KRAS G12C -mutated mCRC patients treated with first-line FOLFIRI or FOLFOX +/- bevacizumab. Both unmatched and propensity-score-matched analysis (PSMA) were conducted, with PSMA controlling for: previous adjuvant chemotherapy, ECOG PS, use of bevacizumab in first line, timing of metastasis appearance, time from diagnosis to first-line start, number of metastatic sites, presence of mucinous component, gender, and age. Subgroup analyses were also performed to investigate subgroup treatment-effect interactions. KRAS G12D -mutated patients were analysed as control., Results: One hundred and four patients treated with irinotecan-(N = 47) or oxaliplatin-based (N = 57) chemotherapy were included. In the unmatched population, objective response rate (ORR) and median (m) progression-free and overall survival (mPFS and mOS) were comparable between the treatment arms. However, a late (>12 months) PFS advantage was observed with irinotecan (HR 0.62, p = 0.02). In the PSMA-derived cohort, a significant improvement with irinotecan vs. oxaliplatin was observed for both PFS and OS: 12- and 24-month PFS rates of 55% vs. 31% and 40% vs. 0% (HR 0.40, p = 0.01) and mOS 37.9 vs. 21.7 months (HR 0.45, p = 0.045), respectively. According to the subgroup analysis, interaction effects between the presence of lung metastases and treatment groups were found in terms of PFS ( p for interaction = 0.08) and OS ( p for interaction = 0.03), with a higher benefit from irinotecan in patients without lung metastases. No difference between treatment groups was observed in the KRAS G12D -mutated cohort (N = 153)., Conclusions: First-line irinotecan-based regimens provided better survival results in KRAS G12C -mutated mCRC patients and should be preferred over oxaliplatin. These findings should also be considered when investigating chemotherapy plus targeted agent combinations.

The growing demand for personalized medicine we are currently witnessing has given rise to more in-depth research in the field of biomarker discovery and, thus, in biological banks that hold the ability to process, collect, store, and distribute "high-quality" biological specimens. However, the notion of "specimen quality" is subject to change with technological advancements. In this perspective, we propose that the notion of sample quality should shift from a broad definition of "high-quality" to a "fit-for-purpose" concept more suitable for precision medicine studies. Digital twins are a digital replica of real entities. These are largely adopted in any digitalized domain and are currently finding applications in biomedicine. The adoption of digital twins for biosamples, proposed in this paper, can provide prompt information about the whole lifecycle of the physical twin (i.e., the biosample) and substantially extend the possible matching criteria between the available samples and the researchers' and physicians' requests. This fine-tuning matching could greatly contribute to improving the "fit-for-purpose" quality, not only for studies based on current needs, but also to improve the identification of the best available samples in future situations, determined by the evolution of technologies and biosciences. Assuming and exploiting a data-science view in our biobank perspective, the more (accurate) data there are available, the more information can be extrapolated from them, the more opportunities there are for matching future, currently unknown, needs. This should be a mandatory principle that the 'time machines' called biobanks should follow., (Copyright © 2023, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Background: Aromatase inhibitors (AI) are widely used for treating hormone-sensitive breast cancer (BC). Obesity, however, due to aromatase-mediated androgen conversion into estradiol in the peripheral adipose tissue, might impair AI inhibitory capacity. We aimed at identifying a cut-off of body mass index (BMI) with significant prognostic impact, in a cohort of stage I-II BC patients on systemic adjuvant therapy with AI. Methods: we retrospectively evaluated routinely collected baseline parameters. The optimal BMI cut-off affecting disease-free survival (DFS) in AI-treated BC patients was identified through maximally selected rank statistics; non-linear association between BMI and DFS in the AI cohort was assessed by hazard-ratio-smoothed curve analysis using BMI as continuous variable. The impact of the BMI cut-off on survival outcomes was estimated through Kaplan−Meier plots, with log-rank test and hazard ratio estimation comparing patient subgroups. Results: A total of 319 BC patients under adjuvant endocrine therapy and/or adjuvant chemotherapy were included. Curve-fitting analysis showed that for a BMI cut-off >29 in AI-treated BC patients (n = 172), DFS was increasingly deteriorating and that the impact of BMI on 2-year DFS identified a cut-off specific only for the cohort of postmenopausal BC patients under adjuvant therapy with AI. Conclusion: in radically resected hormone-sensitive BC patients undergoing neoadjuvant or adjuvant chemotherapy and treated with AI, obesity represents a risk factor for recurrence, with a significantly reduced 2-year DFS.

The approval of larotrectinib and entrectinib for cancer patients harboring an NTRK gene fusion has represented a milestone in the era of "histology-agnostic" drugs. Among the clinical trials that led to the approval of these two drugs, most of the enrolled patients were affected by soft tissue sarcomas, lung, and salivary gland cancer. However, as next-generation sequencing assays are increasingly available in the clinical setting, health care professionals may be able to detect NTRK gene fusions in patients affected by tumor types under or not represented in the clinical trials. To this aim, we systematically reviewed MEDLINE from its inception to 31 August 2022 for case reports and case series on patients with NTRK gene fusion-positive tumors treated with TRK inhibitors. A virtual cohort of 43 patients was created, excluding those enrolled in the above-mentioned clinical trials. Although our results align with those existing in the literature, various cases of central nervous system tumors were registered in our cohort, confirming the benefit of these agents in this subgroup of patients. Large, multi-institutional registries are needed to provide more information about the efficacy of TRK inhibitors in cancer patients affected by tumor types under or not represented in the clinical trials.

Background: Nutritional status is strongly associated to prognosis in metastatic gastrooesophageal junction (mGOJ)/gastric cancer (GC) patients. The aim of the present study was to develop an immune-checkpoint inhibitor (ICI)-specific nutritional index (NI)., Methods: Ten serum and anthropometric nutritional markers derived from blood tests or CT scans were analyzed at baseline in patients treated with second-line ICI and correlated with overall survival (OS). An ICI-specific NI (the NUTRIICI) was developed with its specificity assessed in an independent group of patients treated with standard second-line chemotherapy., Results: From June 2014 to December 2018, 57 mGOJ/GC patients (14 females, 43 males) with a median(m) age of 61 years (range 29-85) received ICI as second-line therapy (Pembrolizumab n=26, Nivolumab n=16, Avelumab n=15). Among the 10 analyzed variables, Onodera's prognostic NI (PNI) ≤33 and waist-to-hip (WHR) <1 were independent predictors of OS and used to build the NUTRIICI. Patients with both favorable factors (i.e., PNI >33 and WHR ≥1, comparator group) had a mOS of 18.0 vs. 6.7 months of patients with one unfavorable factor (either PNI ≤33 or WHR <1, Hazard Ratio, HR 3.06), vs. 1.3 months of patients with both unfavorable factors (HR 17.56), overall P<0.0001. In the independent group of patients treated with standard chemotherapy NUTRIICI was not associated with prognosis (P=0.57)., Conclusions: NUTRIICI is the first ICI-specific NI for mOGJ/GC patients receiving second-line ICI. A validation in larger cohorts is strongly encouraged., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-22-217/coif). The authors have no conflicts of interest to declare., (2022 Journal of Gastrointestinal Oncology. All rights reserved.)

Tailored treatments for metastatic colorectal cancer (mCRC) have not yet completely evolved due to the variety in response to drugs. Therefore, artificial intelligence has been recently used to develop prognostic and predictive models of treatment response (either activity/efficacy or toxicity) to aid in clinical decision making. In this systematic review, we have examined the ability of learning methods to predict response to chemotherapy alone or combined with targeted therapy in mCRC patients by targeting specific narrative publications in Medline up to April 2022 to identify appropriate original scientific articles. After the literature search, 26 original articles met inclusion and exclusion criteria and were included in the study. Our results show that all investigations conducted on this field have provided generally promising results in predicting the response to therapy or toxic side-effects. By a meta-analytic approach we found that the overall weighted means of the area under the receiver operating characteristic (ROC) curve (AUC) were 0.90, 95% C.I. 0.80-0.95 and 0.83, 95% C.I. 0.74-0.89 in training and validation sets, respectively, indicating a good classification performance in discriminating response vs. non-response. The calculation of overall HR indicates that learning models have strong ability to predict improved survival. Lastly, the delta-radiomics and the 74 gene signatures were able to discriminate response vs. non-response by correctly identifying up to 99% of mCRC patients who were responders and up to 100% of patients who were non-responders. Specifically, when we evaluated the predictive models with tests reaching 80% sensitivity (SE) and 90% specificity (SP), the delta radiomics showed an SE of 99% and an SP of 94% in the training set and an SE of 85% and SP of 92 in the test set, whereas for the 74 gene signatures the SE was 97.6% and the SP 100% in the training set.

Precision medicine has opened up a new era in the development of anti-cancer agents that is focused on identifying biomarkers predictive of treatment response regardless of tumor histology. Since 2017, the Food and Drug Administration has approved six drugs with histology-agnostic indications: pembrolizumab (both for tumors with the mismatch-repair deficiency (dMMR)/high microsatellite instability (MSI-H) phenotype and for those with the high tumor mutational burden (TMB-H) phenotype), dostarlimab (for dMMR tumors), larotrectinib and entrectinib (for tumors harboring neurotrophic tyrosine receptor kinase (NTRK) fusions), and the combination of dabrafenib plus trametinib (for BRAF V600E-mutated tumors). The genomic alterations targeted by these antineoplastic agents are rare in metastatic castration-resistant prostate cancer (mCRPC). Furthermore, only a small number of mCRPC patients were enrolled in the clinical trials that led to the approval of the above-mentioned drugs. Therefore, we critically reviewed the literature on the efficacy of histology-agnostic drugs in mCRPC patients. Although the available evidence derives from retrospective studies and case reports, our results confirmed the efficacy of pembrolizumab in dMMR/MSI-H mCRPC. In contrast, few data are available for dostarlimab, larotrectinib, entrectinib, and dabrafenib-trametinib in this subset of patients. Large, multi-institutional registries aimed at collecting real-world data are needed to better comprehend the role of tissue-agnostic drugs in mCRPC patients.

Breast cancer (BC) is the most frequent type of female cancer with increasing incidence in recent years. Doxorubicin (DOX) is an important backbone chemotherapy in BC, responsible for cardiotoxicity (CTX) in about 9% of treated women within the first year. Biomarkers of early CTX diagnosis are essential to avoid complicated DOX-related cardiac diseases. Traditional serum biomarkers are either poorly sensitive with transient elevation, and even absent if investigated outside their diagnostic window, or arise only in late-stage CTX. Emerging biomarkers such as non-coding RNA (ncRNA) have been recently investigated in DOX-related CTX. In our review, we revised the role of microRNAs, the most studied type of ncRNA, both in animal and human models, highlighting the interesting but often contrasting results. Moreover, we reviewed a novel class of ncRNA, circular RNA (circRNA), focusing on their modulatory mechanisms also involving microRNAs. MicroRNA and circRNA are players in a wide homeostatic balance with their perturbation representing a possible compensation for DOX damage. Further studies are required to assess the modalities of early detection of their variation in BC patients suffering from heart disease induced by DOX treatment.

Background: Vitamin D deficiency is a poor prognostic factor in metastatic colorectal cancer (mCRC); however, targeted supplementation trials have so far yielded limited results. We investigated clinical-laboratory parameters influencing vitamin D deficiency, with a particular focus on immune response, and the effect on survival. These parameters could help optimize targeted supplementation therapy. Methods: Association of plasma 25-hydroxyvitamin D (25(OH])D) with overall survival (OS) was assessed with the Hazard Ratio Smoothed Curve with Restricted Cubic Splines (HRSC-RCS) and maximally selected rank statistics (MSRS) in mCRC patients who underwent first-line chemotherapy. Several hematobiochemical variables were evaluated as predictors of vitamin D deficiency by means of Least Absolute Shrinkage and Selection Operator (LASSO) analysis. In a patient subset, peripheral lymphocyte subpopulations were also analyzed. Results: One hundred thirty-three mCRC patients were included. The median(m) baseline 25(OH)D was 10.8 ng/mL (range 3−53.4). HRSC-RCS revealed a linear association between 25(OH)D and OS. MSRS found 10 ng/mL as the optimal 25(OH)D cut-off. The median OS for 25(OH)D < 10 (n = 60) vs. > 10 ng/mL (n = 73) was 12.3 and 24.5 months, respectively (p = 0.002). The LASSO analysis identified high neutrophil-to-lymphocyte ratio (NLR > 3.5) as the strongest predictor of vitamin D deficiency (Odds Ratio 3.35, p 0.0009). Moreover, patients with low 25(OH)D levels (< 10 ng/mL) and high NLR (>3.5) had the shortest survival and patients with 25(OH)D >10 ng/mL and NLR <3.5 had the longest: mOS 8.1 and 28.1 months, respectively, HR 3.40 (1.76−6.59), p 0.0004. Besides the significant difference in NLR between 25(OH)D < and > 10 ng/mL patients (mNLR 3.6 vs. 2.9, p 0.03), the lymphocyte subpopulation analysis revealed that vitamin D deficiency was associated with high T- CD4+ (p = 0.04) and low B (p = 0.03) lymphocyte frequency. Conclusions: NLR is a powerful predictor of Vitamin D deficiency and can further help in stratifying prognosis. Vitamin D deficiency was associated with significant variations in peripheral immune cells. We hypothesize that integrated targeted interventions to both vitamin D and immune system would improve the prognosis of mCRC patients.

Background: KRAS and BRAF mutations are well-established predictive and prognostic factors in metastatic colorectal cancer; however, their impact in the adjuvant setting has not yet been established., Methods: We performed a meta-analysis of adjuvant phase III trials in patients with stage II and III colon cancer with available data on the impact of KRAS or BRAF mutations on both disease-free survival (DFS) and overall survival (OS). Trials were subgrouped based on whether adjustment for microsatellite instability (MSI) was performed and the subgroup effect was analyzed through a meta-regression. To increase the precision of the estimates, a joint DFS-OS (so-called "multivariate") meta-analysis was performed. All statistical tests were 2-sided., Results: Nine trials were selected (QUASAR 2, PETACC-8, N0147, CALGB-89803, NSABP-C07, NSABP-C08, PETACC-3, QUASAR, MOSAIC) including a total of 10 893 patients. In the primary meta-analysis, KRAS mutation was associated with poor DFS (pooled hazard ratio [HR] = 1.36, 95% confidence interval [CI] = 1.15 to 1.61, P < .001) and OS (pooled HR = 1.27, 95% CI = 1.03 to 1.55, P = .03) and BRAF mutation was also associated with poor DFS (pooled HR = 1.33, 95% CI = 1.00 to 1.78, P = .05) and OS (pooled HR = 1.49, 95% CI = 1.31 to 1.70, P < .001). The effect of the mutations on outcome was enhanced in the MSI-adjusted subgroup for both the KRAS mutation (pooled HR for DFS = 1.43, 95% CI = 1.15 to 1.79, P = .001; and pooled HR for OS = 1.33, 95% CI = 1.03 to 1.71, P = .03) and the BRAF mutation (pooled HR for DFS = 1.59, 95% CI = 1.22 to 2.07, P = .001; and pooled HR for OS = 1.67, 95% CI = 1.37 to 2.04, P < .001). The interaction between BRAF and MSI adjustment was statistically significant for DFS (Pinteraction = .02). This interaction was even more pronounced in the DFS-OS multivariate meta-analysis., Conclusions: Both KRAS and BRAF mutations were statistically significantly associated with both DFS and OS, with the mutation effect being enhanced by MSI adjustment. Effective adjuvant treatment for microsatellite-stable BRAF or KRAS-mutated colon cancer represents an unmet clinical need, and exploring the use of recently available BRAF and KRAS inhibitors in this setting would be highly desirable., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Renal cell carcinoma (RCC) associated with anaplastic lymphoma kinase (ALK) gene rearrangements (ALK-RCC) is currently considered an "emerging or provisional" tumor entity by the last World Health Organization classification published in 2016. Although several studies assessing ALK-RCC's clinical and histological characteristics have been published in recent years, only a few publications have evaluated the activity of ALK inhibitors (ALK-i) in this subgroup of patients. Considering the well-recognized efficacy of this evolving class of targeted therapies in other ALK-positive tumors, we conducted a systematic review to evaluate the reported activity of ALK-i in the ALK-RCC subtype. MEDLINE was searched from its inception to 7 January 2022 for case reports and case series on adult metastatic ALK-RCC patients treated with ALK-i whose therapeutic outcomes were available. A virtual cohort of ALK-RCC patients was created. Our results showed a favorable activity of first- and second-generation ALK-i in pretreated ALK-RCC patients in terms of either radiological response or performance status improvement. We hope that the present work will prompt the creation of large, multi-institutional clinical trials to confirm these promising early data.

Objectives: The aim of the present review is to discuss the potential link between RAS, BRAF and microsatellite instability (MSI) mutational patterns and chemotherapeutic agent efficacy [Irinotecan (IRI) vs. Oxaliplatin (OXA)], and how this can potentially influence the choice of the chemotherapy backbone., Methods: Following a review of the research literature, all pertinent articles published in the core journals were selected for the study. The inclusion criteria regarded relevant clinical and pre-clinical studies on the topic of interest (Relationship of OXA and IRI to KRAS/BRAF mutations and MSI)., Results: Excision repair cross complementation group 1 (ERCC1) expression is inhibited by KRAS mutation, making tumor cells more sensitive to OXA. Results from OPUS, COIN and PRIME trials support that no conclusive data are available for BRAF mutant population because of the small number of patients. Enhanced IRI cytotoxicity to MSI cell lines is due to the participation of some of the mismatch repair (MMR) components in various DNA repair processes and their role in the maintenance of the pro-apoptotic effect of IRI and G2/M cell arrest., Conclusion: OXA and IRI are indispensable drugs for mCRC treatment and their selection must be as careful as that of targeted agents. We suggest taking into consideration the interaction between known genomic alterations and OXA and IRI activity to personalize chemotherapy in mCRC patients., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Tumor tissue (T) mutational analysis represents the standard for metastatic colorectal cancer (mCRC); however, circulating tumor DNA (ctDNA) detected by liquid biopsy in plasma (PL) can better represent tumor heterogeneity., Methods: mCRC patients undergoing standard first-line chemotherapy with known T-KRAS/NRAS/BRAF status were enrolled in the present prospective study. PL mutations were assessed within 2 weeks before chemotherapy start with real time PCR and correlated with T status and Progression free survival (PFS). Clinical and biochemical variables including also total number of tumor lesions (TNL) and the sum of maximum diameter (SMD) of all lesions were assessed as potential predictors of T/PL discordance., Results: Among 45 enrolled patients, all BRAF mutations were concordant between T and PL and there were 20% of patients RAS discordant: 9% wild type in T and mutated in PL and 11% mutated in T and wild type in PL. T mutations were significantly associated to median PFS (mPFS of 4.5, 8.3 and 22.9 months for T-BRAF mutated, T-RAS mutated, and T-wild type patients, respectively, p for trend 0.00014). PL mutations further refined prognosis: RAS wild type in T and mutated in PL had significantly shorter PFS than concordant RAS wild type in T and PL: mPFS 9.6 vs. 23.3 months, respectively, p = 0.02. Patients RAS mutated in T and wild type in PL had longer PFS than concordant RAS mutated in T and PL: 24.4 vs. 7.8 months, respectively, p = 0.008. At a multivariate cox regression analysis for PFS, PL mutations were independent prognostic factor superior to T analysis (HR 0.13, p = 0.0008). At multivariate logistic regression analysis TNL and SMD were significant predictors of discordant cases., Conclusions: PL mutational analysis allows a better prognostication than T analysis alone and could help in mCRC treatment management.

Simultaneous care represents the ideal integration between early supportive and palliative care in cancer patients under active antineoplastic treatment. Cancer patients require a composite clinical, social and psychological management that can be effective only if care continuity from hospital to home is guaranteed and if such a care takes place early in the course of the disease, combining standard oncology care and palliative care. In these settings, venous thromboembolism (VTE) represents a difficult medical challenge, for the requirement of acute treatments and for the strong impact on anticancer therapies that might be delayed or, even, totally discontinued. Moreover, cancer patients not only display high rates of VTE occurrence/recurrence but are also more prone to bleeding and this forces clinicians to optimize treatment strategies, balancing between hemorrhages and thrombus formation. VTE prevention is, therefore, regarded as a double-edged sword. Indeed, while on one hand the appropriate use of antithrombotic agents can reduce VTE occurrence, on the other it significantly increases the bleeding risk, especially in the frail patients who present with multiple co-morbidities and poly-therapy that can interact with anticoagulant drugs. For these reasons, thromboprophylaxis should start while active cancer treatment is ongoing, according to a simultaneous care model in a patient-centered perspective.

Machine learning (ML) has been recently introduced to develop prognostic classification models that can be used to predict outcomes in individual cancer patients. Here, we report the significance of an ML-based decision support system (DSS), combined with random optimization (RO), to extract prognostic information from routinely collected demographic, clinical and biochemical data of breast cancer (BC) patients. A DSS model was developed in a training set ( n = 318), whose performance analysis in the testing set ( n = 136) resulted in a C-index for progression-free survival of 0.84, with an accuracy of 86%. Furthermore, the model was capable of stratifying the testing set into two groups of patients with low- or high-risk of progression with a hazard ratio (HR) of 10.9 ( p < 0.0001). Validation in multicenter prospective studies and appropriate management of privacy issues in relation to digital electronic health records (EHR) data are presently needed. Nonetheless, we may conclude that the implementation of ML algorithms and RO models into EHR data might help to achieve prognostic information, and has the potential to revolutionize the practice of personalized medicine.

Risk prediction of chemotherapy-associated venous thromboembolism (VTE) is a compelling challenge in contemporary oncology, as VTE may result in treatment delays, impaired quality of life, and increased mortality. Current guidelines do not recommend thromboprophylaxis for primary prevention, but assessment of the patient's individual risk of VTE prior to chemotherapy is generally advocated. In recent years, efforts have been devoted to building accurate predictive tools for VTE risk assessment in cancer patients. This review focuses on candidate biomarkers and prediction models currently under investigation, considering their advantages and disadvantages, and discussing their diagnostic performance and potential pitfalls.