Promising predictive molecular biomarkers for cervical cancer (Review)

Cervical cancer (CC) constitutes a serious public health problem. Vaccination and screening programs have notably reduced the incidence of CC worldwide by >80%; however, the mortality rate in low‑income countries remains high. The staging of CC is a determining factor in therapeutic strategies: The clinical management of early stages of CC includes surgery and/or radiotherapy, whereas radiotherapy and/or concurrent chemotherapy are the recommended therapeutic strategies for locally advanced CC. The histopathological characteristics of tumors can effectively serve as prognostic markers of radiotherapy response; however, the efficacy rate of radiotherapy may significantly differ among cancer patients. Failure of radiotherapy is commonly associated with a higher risk of recurrence, persistence and metastasis; therefore, radioresistance remains the most important and unresolved clinical problem. This condition highlights the importance of precision medicine in searching for possible predictive biomarkers to timely identify patients at risk of treatment response failure and provide tailored therapeutic strategies according to genetic and epigenetic characteristics. The present review aimed to summarize the evidence that supports the role of several proteins, methylation markers and non‑coding RNAs as potential predictive biomarkers for CC.

Keratin 17 is a prognostic and predictive biomarker in pancreatic ductal adenocarcinoma

OBJECTIVES

To determine the role of keratin 17 (K17) as a predictive biomarker for response to chemotherapy by defining thresholds of K17 expression based on immunohistochemical tests that could be used to optimize therapeutic intervention for patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

We profiled K17 expression, a hallmark of the basal molecular subtype of PDAC, by immunohistochemistry in 2 cohorts of formalin-fixed, paraffin-embedded PDACs (n = 305). We determined a K17 threshold of expression to optimize prognostic stratification according to the lowest Akaike information criterion and explored the potential relationship between K17 and chemoresistance by multivariate predictive analyses.

RESULTS

Patients with advanced-stage, low K17 PDACs treated using 5-fluorouracil (5-FU)-based chemotherapeutic regimens had 3-fold longer survival than corresponding cases treated with gemcitabine-based chemotherapy. By contrast, PDACs with high K17 did not respond to either regimen. The predictive value of K17 was independent of tumor mutation status and other clinicopathologic variables.

CONCLUSIONS

The detection of K17 in 10% or greater of PDAC cells identified patients with shortest survival. Among patients with low K17 PDACs, 5-FU-based treatment was more likely than gemcitabine-based therapies to extend survival.

Neopterin as a potential prognostic and predictive biomarker in metastatic renal cell carcinoma treated with immune checkpoint inhibitors

INTRODUCTION

Immunotherapy represents a significant and essential component of renal carcinoma therapy (RCC), but the selection of an optimal regimen for an individual patient remains unclear. Despite significant improvements in therapeutic options for RCC, predictive biomarkers for immunotherapeutic agents remain elusive. Neopterin is a biomarker of cell-mediated immune response, with concentrations increased in different disorders, including cancer. High neopterin levels herald, in general, a poor prognosis.

AREAS COVERED

This review briefly overviews the contemporary clinical data on biomarkers in metastatic RCC therapy, focusing on neopterin.

EXPERT OPINION

Elevated neopterin levels have been observed in tumors of different primary locations. Research indicates that neopterin may serve as a potential biomarker for assessing the inflammatory status associated with certain cancers. However, it is necessary to interpret neopterin levels in the context of a comprehensive clinical evaluation, as elevated neopterin alone is not specific to cancer and can be influenced by other factors, including comorbid conditions. Neopterin has also been identified as a prognostic biomarker. An increasing neopterin level in serum and urine is associated with advanced cancer, but the role as a potential predictor of response to immunotherapy has yet to be established. A reliable biomarker for optimal therapy selection in metastatic RCC is still putative.

Pharmacogenomic profiling of intra-tumor heterogeneity using a large organoid biobank of liver cancer

Inter- and intra-tumor heterogeneity is a major hurdle in primary liver cancer (PLC) precision therapy. Here, we establish a PLC biobank, consisting of 399 tumor organoids derived from 144 patients, which recapitulates histopathology and genomic landscape of parental tumors, and is reliable for drug sensitivity screening, as evidenced by both in vivo models and patient response. Integrative analysis dissects PLC heterogeneity, regarding genomic/transcriptomic characteristics and sensitivity to seven clinically relevant drugs, as well as clinical associations. Pharmacogenomic analysis identifies and validates multi-gene expression signatures predicting drug response for better patient stratification. Furthermore, we reveal c-Jun as a major mediator of lenvatinib resistance through JNK and β-catenin signaling. A compound (PKUF-01) comprising moieties of lenvatinib and veratramine (c-Jun inhibitor) is synthesized and screened, exhibiting a marked synergistic effect. Together, our study characterizes the landscape of PLC heterogeneity, develops predictive biomarker panels, and identifies a lenvatinib-resistant mechanism for combination therapy.

Early-Stage Non-Small Cell Lung Cancer: Prevalence of Actionable Alterations in a Monocentric Consecutive Cohort

Early-stage (ES) non-small cell lung cancer (NSCLC) is diagnosed in about 30% of cases. The preferred treatment is surgery, but a significant proportion of patients experience recurrence. Neoadjuvant and adjuvant chemotherapy has a limited clinical benefit. EGFR tyrosine kinase inhibitors and immunotherapy have recently opened new therapeutic scenarios. However, only a few data are available about the ES-NSCLC molecular landscape and the impact of oncogene addiction on therapy definition. Here, we determined the prevalence of the main lung cancer driver alterations in a monocentric consecutive cohort. Molecular analysis was performed on 1122 cases, including 368 ES and 754 advanced NSCLC. The prevalence of actionable alterations was similar between early and advanced stages. ES-NSCLC was significantly enriched for MET exon-14 skipping alterations and presented a lower prevalence of BRAF p.(V600E) mutation. PD-L1 expression levels, evaluated according to actionable alterations, were higher in advanced than early tumors harboring EGFR, KRAS, MET alterations and gene fusions. Taken together, these results confirm the value of biomarker testing in ES-NSCLC. Although approved targeted therapies for ES-NSCLC are still limited, the identification of actionable alterations could improve patients' selection for immunotherapy, favoring the enrollment in clinical trials and allowing a faster treatment start at disease recurrence.

Biomarkers for prediction of CAR T therapy outcomes: current and future perspectives

Chimeric antigen receptor (CAR) T cell therapy holds enormous potential for the treatment of hematologic malignancies. Despite its benefits, it is still used as a second line of therapy, mainly because of its severe side effects and patient unresponsiveness. Numerous researchers worldwide have attempted to identify effective predictive biomarkers for early prediction of treatment outcomes and adverse effects in CAR T cell therapy, albeit so far only with limited success. This review provides a comprehensive overview of the current state of predictive biomarkers. Although existing predictive metrics correlate to some extent with treatment outcomes, they fail to encapsulate the complexity of the immune system dynamics. The aim of this review is to identify six major groups of predictive biomarkers and propose their use in developing improved and efficient prediction models. These groups include changes in mitochondrial dynamics, endothelial activation, central nervous system impairment, immune system markers, extracellular vesicles, and the inhibitory tumor microenvironment. A comprehensive understanding of the multiple factors that influence therapeutic efficacy has the potential to significantly improve the course of CAR T cell therapy and patient care, thereby making this advanced immunotherapy more appealing and the course of therapy more convenient and favorable for patients.

Neoadjuvant chemohormonal therapy before radical prostatectomy in high-risk prostate cancer: a mini-review

High-risk localized prostate cancer (PCa) has the potential of recurrence and progression to a lethal phenotype, and neoadjuvant therapy followed by radical prostatectomy (RP) may be an option for these patients. Docetaxel has been recently shown to be an effective chemotherapeutic agent for high-volume metastatic hormone-sensitive PCa and metastatic castration-resistant PCa, and these increased efficacy create the impetus to assess the potential role of preoperative docetaxel in high-risk localized PCa. In this mini-review, we found that neoadjuvant chemohormonal therapy (NCHT) may be an effective neoadjuvant regimen to improve oncological outcome of high-risk PCa. However, the addition of docetaxel in the neoadjuvant setting would unavoidably increase the rate of adverse events, impose additional economic burdens. Therefore, suitable patient selection is crucial and pathological response might be a surrogate endpoint. Furthermore, we also found that molecular imaging prostate-specific membrane antigen (PSMA) PET/CT was a promising tool to evaluation the effectiveness of NCHT, and the expression status of AR, AR-V7, Ki-67, PTEN and TP53 might be helpful for urologists to identify more suitable candidates for NCHT.

Tumor Copy Number Alteration Burden as a Predictor for Resistance to Immune Checkpoint Blockade across Different Cancer Types

Immune checkpoint blockade (ICB) benefits only a subset of advanced cancer patients, and predictive biomarkers for immunotherapy response are needed. Recently, copy number alteration (CNA) burden has been proposed to predict ICB resistance. We assessed this finding using the publicly accessible data for 1661 ICB-treated patients whose tumors were profiled by MSK-IMPACT, an approved targeted assay in clinical care. We tested the hypothesis that the continuous increase in CNA burden is associated with poor overall survival following ICB. In addition, we hypothesized that the combinatorial biomarkers of tumor mutational burden (TMB) and CNA burden would better stratify patients for immune status and ICB response. Of the 1661 cases, 79% (n = 1307) were treated with anti PD-1/PD-L1 and the remaining 21% (n = 354) with anti CTLA-4 or the combination of both. In a multivariate analysis, increase in CNA burden was associated with poor overall survival [HR = 1.52, 95% CI (1.01-2.30), p = 0.04]. The combination of biomarkers TMB and CNA burden stratified patients into four clinically distinct subsets among which "LowTMB/HighCNA" showed the worst survival (p < 0.0001). The four patient subsets had unique CNA profiles and enriched pathways, which could predict transcriptional and phenotypic effects related to immune signaling and CD8+ T-cell abundance in the tumor microenvironment. CNA burden was associated with poor overall survival in patients receiving ICB and could improve patient stratification when incorporated with TMB. These findings may guide patient selection for immunotherapy or alternative strategies.

Clinical and biomarker analyses of hepatic arterial infusion chemotherapy plus lenvatinib and PD-1 inhibitor for patients with advanced intrahepatic cholangiocarcinoma

Background

Intrahepatic cholangiocarcinoma (iCCA) is a highly aggressive cancer with a dismal prognosis and few effective therapeutic approaches. This study aimed to investigate the efficacy, safety, and predictive biomarkers of hepatic arterial infusion chemotherapy (FOLFOX-HAIC) in combination with lenvatinib and PD-1 inhibitor for patients with advanced iCCA.

Methods

Locally advanced or metastatic iCCA patients receiving the triple combination therapy of lenvatinib, PD-1 inhibitor, and FOLFOX-HAIC were included in this retrospective study. Primary endpoint was the progression-free survival, evaluated using the RECIST criterion. The secondary endpoints included overall survival, objective response rate, and safety. Whole exome and RNA sequencing of tumor biopsy tissues were performed for biomarker exploration.

Results

Between May, 2019 and December 2022, a total of 46 patients were included in this study. The primary endpoint showed a median progression-free survival of 9.40 months (95% CI: 5.28-13.52), with a 6-month progression-free survival rate of 76.1%. The median overall survival was 16.77 months (95% CI, 14.20-19.33), with an objective response rate of 47.8% and disease control rate of 91.3% per RECIST. In addition, 4.3% and 8.7% of patients achieved complete response of all lesions and intrahepatic target lesions per mRECIST, respectively. The most common treatment-related adverse events were neutropenia, thrombocytopenia, elevated aspartate aminotransferase and alanine aminotransferase level. Furthermore, integrated analysis of genetic, transcriptomic, and immunohistochemistry data revealed that pre-existing immunity (high expression level of immune-related signatures and intra-tumoral CD8+ T cell density) in baseline tumor tissues was associated with superior clinical benefits. However, the evaluation of tumor mutation burden did not show potential predictive value in this triple combination.

Conclusion

FOLFOX-HAIC in combination with lenvatinib and PD-1 inhibitor demonstrated a promising antitumor activity with manageable safety profiles in patients with advanced iCCA. Moreover, our study also revealed new perspectives on potential biomarkers for clinical efficacy.

Optimizing tissue stewardship in non-small cell lung cancer to support molecular characterization and treatment selection: statement from a working group of thoracic pathologists

Many patients with non-small cell lung cancer do not receive guideline-recommended, biomarker-directed therapy, despite the potential for improved clinical outcomes. Access to timely, accurate, and comprehensive molecular profiling, including targetable protein overexpression, is essential to allow fully informed treatment decisions to be taken. In turn, this requires optimal tissue management to protect and maximize the use of this precious finite resource. Here, a group of leading thoracic pathologists recommend factors to consider for optimal tissue management. Starting from when lung cancer is first suspected, keeping predictive biomarker testing in the front of the mind should drive the development of practices and procedures that conserve tissue appropriately to support molecular characterization and treatment selection.

Overcoming Chemotherapy Resistance in Metastatic Cancer: A Comprehensive Review

The management of metastatic cancer is complicated by chemotherapy resistance. This manuscript provides a comprehensive academic review of strategies to overcome chemotherapy resistance in metastatic cancer. The manuscript presents background information on chemotherapy resistance in metastatic cancer cells, highlighting its clinical significance and the current challenges associated with using chemotherapy to treat metastatic cancer. The manuscript delves into the molecular mechanisms underlying chemotherapy resistance in subsequent sections. It discusses the genetic alterations, mutations, and epigenetic modifications that contribute to the development of resistance. Additionally, the role of altered drug metabolism and efflux mechanisms, as well as the activation of survival pathways and evasion of cell death, are explored in detail. The strategies to overcome chemotherapy resistance are thoroughly examined, covering various approaches that have shown promise. These include combination therapy approaches, targeted therapies, immunotherapeutic strategies, and the repurposing of existing drugs. Each strategy is discussed in terms of its rationale and potential effectiveness. Strategies for early detection and monitoring of chemotherapy drug resistance, rational drug design vis-a-vis personalized medicine approaches, the role of predictive biomarkers in guiding treatment decisions, and the importance of lifestyle modifications and supportive therapies in improving treatment outcomes are discussed. Lastly, the manuscript outlines the clinical implications of the discussed strategies. It provides insights into ongoing clinical trials and emerging therapies that address chemotherapy resistance in metastatic cancer cells. The manuscript also explores the challenges and opportunities in translating laboratory findings into clinical practice and identifies potential future directions and novel therapeutic avenues. This comprehensive review provides a detailed analysis of strategies to overcome chemotherapy resistance in metastatic cancer. It emphasizes the importance of understanding the molecular mechanisms underlying resistance and presents a range of approaches for addressing this critical issue in treating metastatic cancer.

Optimization of cancer immunotherapy on the basis of programmed death ligand-1 distribution and function

Programmed cell death protein-1 (PD-1)/programmed death ligand-1 (PD-L1) immune checkpoint blockade as a breakthrough in cancer immunotherapy has shown unprecedented positive outcomes in the clinic. However, the overall effectiveness of PD-L1 antibody is less than expected. An increasing number of studies have demonstrated that PD-L1 is widely distributed and expressed not only on the cell membrane but also on the inside of the cells as well as on the extracellular vesicles secreted by tumour cells. Both endogenous and exogenous PD-L1 play significant roles in influencing the therapeutic effect of anti-tumour immunity. Herein, we mainly focused on the distribution and function of PD-L1 and further summarized the potential targeted therapeutic strategies. More importantly, in addition to taking the overall expression abundance of PD-L1 as a predictive indicator for selecting corresponding PD-1/PD-L1 monoclonal antibodies (mAbs), we also proposed that personalized combination therapies based on the different distribution of PD-L1 are worth attention to achieve more efficient and effective therapeutic outcomes in cancer patients. LINKED ARTICLES: This article is part of a themed issue on Cancer Microenvironment and Pharmacological Interventions. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.2/issuetoc.

Predictive Value of the Interaction between CEA and Hemoglobin in Neoadjuvant CCRT Outcomes in Rectal Cancer Patients

The adoption of neoadjuvant concurrent chemoradiotherapy (CCRT) has reshaped the therapeutic landscape, but response prediction remains challenging. This study investigates the interaction between pre-CCRT carcinoembryonic antigen (CEA) and post-CCRT hemoglobin (Hb) levels in predicting the response of locally advanced rectal cancer (LARC) to CCRT. Retrospective data from 93 rectal cancer patients receiving neoadjuvant CCRT were analyzed. Univariate analyses assessed clinical factors associated with tumor regression grade (TRG) and T-stage outcomes. Machine learning identified predictive biomarkers. Interaction effects between CEA and Hb were explored through subgroup analyses. Post-CCRT Hb varied between pre-CCRT CEA groups. The interaction between pre-CCRT CEA and post-CCRT Hb influenced TRG. Males with normal pre-CCRT CEA and anemia showed better treatment responses. Females with elevated pre-CCRT CEA and post-CCRT anemia exhibited poorer responses. The interaction effect between them was significant, indicating that their relationship with TRG was not additive. Inflammatory biomarkers, WBC, neutrophil count, and post-CCRT platelet level correlated with CCRT response. Contrasting with previous findings, anemia was a predictor of better treatment response in males with normal pre-CCRT CEA. The interaction between pre-CCRT CEA and post-CCRT Hb levels predicts the response of LARC to CCRT. CEA, Hb, and sex should be considered when assessing treatment response. Inflammatory biomarkers contribute to response prediction. Understanding these complex relationships can enhance personalized treatment approaches in rectal cancer patients.

Is platelet to lymphocyte ratio predictive of preeclampsia? A systematic review and meta-analysis

BACKGROUND

To evaluate the value of the platelet-to-lymphocyte ratio (PLR) in predicting preeclampsia (PE) in pregnant women.

METHODS

PubMed, EMBASE and Web of Science databases were searched for observational studies (cohort, case-control or cross-sectional) that reported pre-treatment maternal PLR values in women with and without PE. The analysis was done using a random effects model. Pooled effect sizes were reported as weighted mean difference (WMD) with 95% confidence intervals (CIs). Newcastle-Ottawa Scale (NOS) was used to evaluate the risk of bias.

RESULTS

Twenty-five studies with 7755 patients were included in this meta-analysis. PLR was comparable in patients with PE and healthy pregnant women (WMD -2.97; 95% CI: -11.95 to 6.02; N = 16). Patients with mild (WMD -3.00; 95% CI: -17.40 to 11.41; N = 12) and severe PE (WMD -5.77; 95% CI: -25.48 to 13.94; N = 14) had statistically similar PLR, compared to healthy controls.

CONCLUSIONS

Our findings show similar PLR in PE and healthy pregnancies. PLR, therefore, may not be used to differentiate between PE and normal pregnancy or for assessing the severity of PE. The majority of included studies were case-control, potentially introducing bias, and we identified evidence of publication bias as well.

Treatment of acute myeloid leukaemia in older patients - scope of intensive therapy? - A retrospective analysis

PURPOSE

Therapeutic regimens and outcome of acute myeloid leukaemia (AML) patients substantially improved over the past decades. However, AML in older patients is still widely understudied and therapeutic standards are far less well defined. This study provides a retrospective analysis of a cohort of AML patients above 65 years of age treated at a single university centre in Germany.

METHODS

Treatment regimens including intensive chemotherapy with or without subsequent allogenic stem cell transplantation (allo-SCT), hypomethylating agent (HMA) or low-dose cytarabine (LD-AraC) based therapy or best supportive care (BSC) were evaluated and compared to patient-specific variables, comorbidities indices such as Haematopoietic Cell Transplantation-specific Comorbidity Index (HCT-CI) or Charlson Comorbidity Index (CCI), or Eastern Cooperative Oncology Group (ECOG) performance status to assess their potential impact on outcome.

RESULTS

229 patients ≥ 65 years with newly diagnosed AML were included in this study. Patients received either intensive chemotherapy (IT) without (n = 101, 44%), or followed by allo-SCT (n = 27, 12%), HMA (n = 29, 13%), LD-Ara-C (n = 16, 7%) or best supportive care (BSC) only (n = 56, 24%). Of interest, ECOG performance status predicted overall survival in patients treated with IT, and combinatorial assessment of ECOG and HCT-CI was particularly useful to predict outcome in this subgroup of patients.

CONCLUSION

Subsets of AML patients above 65 years of age benefit from intensive chemotherapy and allogenic stem cell transplantation. Combined assessment of ECOG scores and HCT-CI might help to objectively identify suitable patients, and this concept should be further investigated in a prospective manner in future studies.

Exploring the Potential of Olfactory Receptor Circulating RNA Measurement for Preeclampsia Prediction and Its Linkage to Mild Gestational Hypothyroidism

Gestational hypothyroidism may lead to preeclampsia development. However, this pathophysiological is unknown. We expect to find a shared mechanism by comparing hypothyroidism and preeclampsia. From our transcriptome data, we recognized olfactory receptors as that fingerprint. The reduction of taste and smell in hypothyroid patients has been known for a long time. Therefore, we decided to look to the olfactory receptors and aimed to identify genes capable of predicting preeclampsia (PEC). Methods: An Ion Proton Sequencer (Thermo Fisher Scientific, Waltham, MA, USA) was used to construct the transcriptome databases. RStudio with packages Limma v.3.50.0, GEOquery v.2.62.2, and umap v.0.2.8.8 were used to analyze the differentially expressed genes in GSE149440 from the Gene Expression Omnibus (GEO). The 7500 Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) was used for RT-qPCR amplification of OR6X1 and OR4E2. Results: Our transcriptomic datasets analysis revealed 25.08% and 26.75% downregulated olfactory receptor (ORs) in mild nontreated gestational hypothyroidism (GHT) and PEC, respectively. In the GSE149440 GEO dataset, we found OR5H1, OR5T3, OR51A7, OR51B6, OR10J5, OR6C6, and OR2AG2 as predictors of early-onset PEC. We also evaluate two chosen biomarkers' responses to levothyroxine. The RT-qPCR demonstrated a difference in OR6X1 and OR4E2 expression between GHT and healthy pregnancy (p < 0.05). Those genes presented a negative correlation with TSH (r: -0.51, p < 0.05; and r: -0.44, p < 0.05), a strong positive correlation with each other (r: 0.89; p < 0.01) and the levothyroxine-treated group had no difference from the healthy one. We conclude that ORs could be used as biomarkers at the beginning of gestation, and the downregulated ORs found in GHT may be improved with levothyroxine treatment.

Real-World Outcomes of Immunotherapy in Second- or Later-Line Non-Small Cell Lung Cancer with Actionable Genetic Alterations

INTRODUCTION

While the efficacy of immune checkpoint inhibitors (ICIs) in treating non-small cell lung cancer (NSCLC) patients with actionable genetic alterations (AGAs) is modest, certain patients demonstrate improved survival. Thus, this study aimed to evaluate the benefits of ICIs in NSCLC patients with diverse AGAs and verify the predictive biomarkers of ICI efficacy.

METHODS

From January 2018 to July 2022, this study compared the progression-free survival (PFS) of NSCLC patients with different AGAs treated with ICI monotherapy as second- or later-line therapy at Samsung Medical Center. To ascertain the predictors of ICIs efficacy, we adjusted ICIs' effects on PFS in terms of clinical and molecular biomarkers.

RESULTS

EGFR (46.0%) was the most prevalent mutation in 324 patients. In multivariate analysis, PD-L1 positivity (tumor proportion score (TPS) ≥ 1%) (HR = 0.41) and the use of steroids for immune-related adverse events (HR = 0.46) were positive factors for ICI therapy in the AGAs group. Co-existing mutation of STK11 with KRAS mutation (HR = 4.53) and TP53 with MET mutation (HR = 9.78) was negatively associated with survival.

CONCLUSIONS

The efficacy of ICI treatment varied across AGA subtypes, but patients with KRAS, MET, and BRAF mutations demonstrated relatively long-duration benefits of ICI therapy. PD-L1 was a significant positive predictive biomarker in all AGA groups.

Predictive Biomarkers of Treatment Response in Major Depressive Disorder

Major depressive disorder (MDD) is a highly prevalent, debilitating disorder with a high rate of treatment resistance. One strategy to improve treatment outcomes is to identify patient-specific, pre-intervention factors that can predict treatment success. Neurophysiological measures such as electroencephalography (EEG), which measures the brain's electrical activity from sensors on the scalp, offer one promising approach for predicting treatment response for psychiatric illnesses, including MDD. In this study, a secondary data analysis was conducted on the publicly available Two Decades Brainclinics Research Archive for Insights in Neurophysiology (TDBRAIN) database. Logistic regression modeling was used to predict treatment response, defined as at least a 50% improvement on the Beck's Depression Inventory, in 119 MDD patients receiving repetitive transcranial magnetic stimulation (rTMS). The results show that both age and baseline symptom severity were significant predictors of rTMS treatment response, with older individuals and more severe depression scores associated with decreased odds of a positive treatment response. EEG measures contributed predictive power to these models; however, these improvements in outcome predictability only trended towards statistical significance. These findings provide confirmation of previous demographic and clinical predictors, while pointing to EEG metrics that may provide predictive information in future studies.

Predicting Response to Antibody Drug Conjugates: A Focus on Antigens' Targetability

Antibody-drug conjugates (ADCs) represent a cornerstone in the treatment of many cancers nowadays. ADCs fulfill their function by binding a target on tumor cell membrane to deliver a cytotoxic payload; in addition, those moieties capable of crossing cancer cell membranes can achieve near-by cells that do not express the target antigen, exerting the so-called "bystander" cytotoxic effect. The presence of a specific target antigen expressed on cancer cells has been for long considered crucial for ADCs and commonly required for the inclusion of patients in clinical trials with ADCs. To date, only ado-trastuzumab-emtansine, fam-trastuzumab deruxtecan-nxki, and mirvetuximab soravtansine-gynx are approved according to the expression of a target antigen in solid tumors, while the clinical use of other ADCs (eg, sacituzumab govitecan) is not conditioned by the presence of a specific biomarker. Given the ever-growing number of approved ADCs and those under investigation, it is essential to find new biomarkers to guide their use, especially in those settings for which different ADCs are approved to establish the best therapeutic sequence based on robust biomarkers. Hence, this work addresses the role of target antigens in predicting response to ADCs, focusing on examples of antigens' targetability according to their expression on cancer cells' surface or to the presence of specific target aberrations (eg, mutation or over-expression). New methods for the assessment and quantification of targets' expression, like molecular imaging and in vitro assays, might be key tools to improve biomarker analysis and eventually deliver better outcomes by refined patient selection.

A pan-cancer clinical platform to predict immunotherapy outcomes and prioritize immuno-oncology combinations in early-phase trials

BACKGROUND

Immunotherapy is effective, but current biomarkers for patient selection have proven modest sensitivity. Here, we developed VIGex, an optimized gene signature based on the expression level of 12 genes involved in immune response with RNA sequencing.

METHODS

We implemented VIGex using the nCounter platform (Nanostring) on a large clinical cohort encompassing 909 tumor samples across 45 tumor types. VIGex was developed as a continuous variable, with cutoffs selected to detect three main categories (hot, intermediate-cold and cold) based on the different inflammatory status of the tumor microenvironment.

FINDINGS

Hot tumors had the highest VIGex scores and exhibited an increased abundance of tumor-infiltrating lymphocytes as compared with the intermediate-cold and cold. VIGex scores varied depending on tumor origin and anatomic site of metastases, with liver metastases showing an immunosuppressive tumor microenvironment. The predictive power of VIGex-Hot was observed in a cohort of 98 refractory solid tumor from patients treated in early-phase immunotherapy trials and its clinical performance was confirmed through an extensive metanalysis across 13 clinically annotated gene expression datasets from 877 patients treated with immunotherapy agents. Last, we generated a pan-cancer biomarker platform that integrates VIGex categories with the expression levels of immunotherapy targets under development in early-phase clinical trials.

CONCLUSIONS

Our results support the clinical utility of VIGex as a tool to aid clinicians for patient selection and personalized immunotherapy interventions.

FUNDING

BBVA Foundation; 202-2021 Division of Medical Oncology and Hematology Fellowship award; Princess Margaret Cancer Center.

Comprehensive Systematic Review of Biomarkers in Metastatic Renal Cell Carcinoma: Predictors, Prognostics, and Therapeutic Monitoring

BACKGROUND

Challenges remain in determining the most effective treatment strategies and identifying patients who would benefit from adjuvant or neoadjuvant therapy in renal cell carcinoma. The objective of this review is to provide a comprehensive overview of biomarkers in metastatic renal cell carcinoma (mRCC) and their utility in prediction of treatment response, prognosis, and therapeutic monitoring in patients receiving systemic therapy for metastatic disease.

METHODS

A systematic literature search was conducted using the PubMed database for relevant studies published between January 2017 and December 2022. The search focused on biomarkers associated with mRCC and their relationship to immune checkpoint inhibitors, targeted therapy, and VEGF inhibitors in the adjuvant, neoadjuvant, and metastatic settings.

RESULTS

The review identified various biomarkers with predictive, prognostic, and therapeutic monitoring potential in mRCC. The review also discussed the challenges associated with anti-angiogenic and immune-checkpoint monotherapy trials and highlighted the need for personalized therapy based on molecular signatures.

CONCLUSION

This comprehensive review provides valuable insights into the landscape of biomarkers in mRCC and their potential applications in prediction of treatment response, prognosis, and therapeutic monitoring. The findings underscore the importance of incorporating biomarker assessment into clinical practice to guide treatment decisions and improve patient outcomes in mRCC.

Skin surface biomarkers are associated with future development of atopic dermatitis in children with family history of allergic disease

BACKGROUND

Atopic dermatitis (AD) is a common childhood chronic inflammatory skin disorder that can significantly impact quality of life and has been linked to the subsequent development of food allergy, asthma, and allergic rhinitis, an association known as the "atopic march."

OBJECTIVE

The aim of this study was to identify biomarkers collected non-invasively from the skin surface in order to predict AD before diagnosis across a broad age range of children.

METHODS

Non-invasive skin surface measures and biomarkers were collected from 160 children (3-48 months of age) of three groups: (A) healthy with no family history of allergic disease, (B) healthy with family history of allergic disease, and (C) diagnosed AD.

RESULTS

Eleven of 101 children in group B reported AD diagnosis in the subsequent 12 months following the measurements. The children who developed AD had increased skin immune markers before disease onset, compared to those who did not develop AD in the same group and to the control group. In those enrolled with AD, lesional skin was characterized by increased concentrations of certain immune markers and transepidermal water loss, and decreased skin surface hydration.

CONCLUSIONS

Defining risk susceptibility before onset of AD through non-invasive methods may help identify children who may benefit from early preventative interventions.

Biomarkers for Immunotherapy in Driver-Gene-Negative Advanced NSCLC

Outcome improvement in patients with driver-gene-negative advanced non-small cell lung cancer (NSCLC) has been significantly enhanced through targeting the immune system, specifically the PD-L1/PD-1 axis. Nevertheless, only a subset of patients with advanced NSCLC may derive benefits from immuno-monotherapy or immunotherapy combined with chemotherapy. Hence, in order to identify patients who will gain the maximum advantage from immunotherapy, it is crucial to investigate predictive biomarkers. This review provides a summary of the currently identified biomarkers associated with the extent of benefit from immuno-monotherapy or immunotherapy combined with chemotherapy in patients with advanced NSCLC. These biomarkers can be categorized into three groups: tumor-related, tumor-microenvironment-related, and host-factor-related.Tumor-related factors include PD-L1 expression, tumor mutational burden and specific genetic mutations, while tumor-microenvironment-related factors include extracellular vesicles and T-cell receptors, and host-related factors include systemic inflammation, circulating fatty acid profile, and the microbiome.

Prognostic Implications of Clinical, Laboratory and Echocardiographic Biomarkers in Patients with Acute Myocardial Infarction-Rationale and Design of the ''CLEAR-AMI Study''

BACKGROUND

Acute myocardial infarction (AMI) remains a major cause of death worldwide. Survivors of AMI are particularly at high risk for additional cardiovascular events. Consequently, a comprehensive approach to secondary prevention is necessary to mitigate the occurrence of downstream complications. This may be achieved through a multiparametric tailored risk stratification by incorporating clinical, laboratory and echocardiographic parameters.

METHODS

The ''CLEAR-AMI Study'' (ClinicalTrials.gov Identifier: NCT05791916) is a non-interventional, prospective study including consecutive patients with AMI without a known history of coronary artery disease. All patients satisfying these inclusion criteria are enrolled in the present study. The rationale of this study is to refine risk stratification by using clinical, laboratory and novel echocardiographic biomarkers. All the patients undergo a comprehensive transthoracic echocardiographic assessment, including strain and myocardial work analysis of the left and right heart chambers, within 48 h of admission after coronary angiography. Their laboratory profile focusing on systemic inflammation is captured during the first 24 h upon admission, and their demographic characteristics, past medical history, and therapeutic management are recorded. The angioplasty details are documented, the non-culprit coronary lesions are archived, and the SYNTAX score is employed to evaluate the complexity of coronary artery disease. A 24-month follow-up period will be recorded for all patients recruited.

CONCLUSION

The ''CLEAR-AMI" study is an ongoing prospective registry endeavoring to refine risk assessment in patients with AMI without a known history of coronary artery disease, by incorporating echocardiographic parameters, biochemical indices, and clinical and coronary characteristics in the acute phase of AMI.

Pre-treatment Amino Acids and Risk of Paclitaxel-induced Peripheral Neuropathy in SWOG S0221

Background

Chemotherapy-induced peripheral neuropathy (CIPN) is a treatment-limiting and debilitating neurotoxicity of many commonly used anti-cancer agents, including paclitaxel. The objective of this study was to confirm the previously found inverse association between pre-treatment blood concentrations of histidine and CIPN occurrence and examine relationships of other amino acids with CIPN severity.

Methods

Pre-treatment levels of 20 amino acid concentrations were measured via a targeted mass spectrometry assay in banked serum from the SWOG S0221 (NCT00070564) trial of patients with early-stage breast cancer receiving paclitaxel. The associations between amino acid levels and CIPN occurrence or severity were tested in regression analysis adjusted for paclitaxel schedule, age, self-reported race, and body mass index with Bonferroni correction for multiple comparisons. The network of metabolic pathways of amino acids was analyzed using over-representation analysis in MetaboAnalyst. The partial correlation network of amino acids was evaluated using a debiased sparse partial correlation algorithm and Cytoscape.

Results

In the primary analysis, histidine concentration was not associated with CIPN occurrence (odds ratio (OR) = 0.97 [0.83, 1.13], p = 0.72). In a secondary analysis, no amino acid was associated with CIPN occurrence (all p > 0.0025). Higher concentrations of four amino acids, glutamate (β = 0.58 [0.23, 0.93], p = 0.001), phenylalanine (β = 0.54 [0.19, 0.89], p = 0.002), tyrosine (β = 0.57 [0.23, 0.91], p = 0.001), and valine (β = 0.58 [0.24, 0.92], p = 0.001) were associated with more severe CIPN, but none of these associations retained significance after adjustment. In the over-representation analysis, no amino acid metabolic pathways were significantly enriched (all FDR > 0.05). In the network of enriched pathways, glutamate metabolism had the highest centrality.

Conclusions

This analysis showed that pre-treatment serum amino acid concentrations are not strongly predictive of CIPN severity. Future prospectively designed studies that assess non-amino acid metabolomics predictors are encouraged.

CD4 T cells and toxicity from immune checkpoint blockade

Immune-related toxicities, otherwise known as immune-related adverse events (irAEs), occur in a substantial fraction of cancer patients treated with immune checkpoint inhibitors (ICIs). Ranging from asymptomatic to life-threatening, ICI-induced irAEs can result in hospital admission, high-dose corticosteroid treatment, ICI discontinuation, and in some cases, death. A deeper understanding of the factors underpinning severe irAE development will be essential for improved irAE prediction and prevention, toward maximizing the benefits and safety profiles of ICIs. In recent work, we applied mass cytometry, single-cell RNA sequencing, single-cell V(D)J sequencing, bulk RNA sequencing, and bulk T-cell receptor (TCR) sequencing to identify pretreatment determinants of severe irAE development in patients with advanced melanoma. Across 71 patients separated into three cohorts, we found that two baseline features in circulation-elevated activated CD4 effector memory T-cell abundance and TCR diversity-are associated with severe irAE development, independent of the affected organ system within 3 months of ICI treatment initiation. Here, we provide an extended perspective on this work, synthesize and discuss related literature, and summarize practical considerations for clinical translation. Collectively, these findings lay a foundation for data-driven and mechanistic insights into irAE development, with the potential to reduce ICI morbidity and mortality in the future.

Exploring novel genetic and hematological predictors of response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer

Introduction: The standard treatment for locally advanced rectal cancer (LARC) is neoadjuvant chemoradiotherapy (nCRT). To select patients who would benefit the most from nCRT, there is a need for predictive biomarkers. The aim of this study was to evaluate the role of clinical, pathological, radiological, inflammation-related genetic, and hematological parameters in the prediction of post-nCRT response. Materials and methods: In silico analysis of published transcriptomics datasets was conducted to identify candidate genes, whose expression will be measured using quantitative Real Time PCR (qRT-PCR) in pretreatment formaline-fixed paraffin-embedded (FFPE) samples. In this study, 75 patients with LARC were prospectively included between June 2020-January 2022. Patients were assessed for tumor response in week 8 post-nCRT with pelvic MRI scan and rigid proctoscopy. For patients with a clinical complete response (cCR) and initially distant located tumor no immediate surgery was suggested ("watch and wait" approach). The response after surgery was assessed using histopathological tumor regression grading (TRG) categories from postoperative specimens by Mandard. Responders (R) were defined as patients with cCR without operative treatment, and those with TRG 1 and TRG 2 postoperative categories. Non-responders (NR) were patients classified as TRG 3-5. Results: Responders group comprised 35 patients (46.6%) and NR group 53.4% of patients. Analysis of published transcriptomics data identified genes that could predict response to treatment and their significance was assessed in our cohort by qRT-PCR. When comparison was made in the subgroup of patients who were operated (TRG1 vs. TRG4), the expression of IDO1 was significantly deregulated (p < 0.05). Among hematological parameters between R and NR a significant difference in the response was detected for neutrophil-to-monocyte ratio (NMR), initial basophil, eosinophil and monocyte counts (p < 0.01). According to MRI findings, non-responders more often presented with extramural vascular invasion (p < 0.05). Conclusion: Based on logistic regression model, factors associated with favorable response to nCRT were tumor morphology and hematological parameters which can be easily and routinely derived from initial laboratory results (NMR, eosinophil, basophil and monocyte counts) in a minimally invasive manner. Using various metrics, an aggregated score of the initial eosinophil, basophil, and monocyte counts demonstrated the best predictive performance.

Circulating Tumour Cell Associated MicroRNA Profiles Change during Chemoradiation and Are Predictive of Response in Locally Advanced Rectal Cancer

Locally advanced rectal cancer (LARC) has traditionally been treated with trimodality therapy consisting of neoadjuvant radiation +/- chemotherapy, surgery, and adjuvant chemotherapy. There is currently a clinical need for biomarkers to predict treatment response and outcomes, especially during neoadjuvant therapy. Liquid biopsies in the form of circulating tumour cells (CTCs) and circulating nucleic acids in particular microRNAs (miRNA) are novel, the latter also being highly stable and clinically relevant regulators of disease. We studied a prospective cohort of 52 patients with LARC, and obtained samples at baseline, during treatment, and post-treatment. We enumerated CTCs during chemoradiation at these three time-points, using the IsofluxTM (Fluxion Biosciences Inc., Alameda, CA, USA) CTC Isolation and detection platform. We then subjected the isolated CTCs to miRNA expression analyses, using a panel of 106 miRNA candidates. We identified CTCs in 73% of patients at baseline; numbers fell and miRNA expression profiles also changed during treatment. Between baseline and during treatment (week 3) time-points, three microRNAs (hsa-miR-95, hsa-miR-10a, and hsa-miR-16-1*) were highly differentially expressed. Importantly, hsa-miR-19b-3p and hsa-miR-483-5p were found to correlate with good response to treatment. The latter (hsa-miR-483-5p) was also found to be differentially expressed between good responders and poor responders. These miRNAs represent potential predictive biomarkers, and thus a potential miRNA-based treatment strategy. In this study, we demonstrate that CTCs are present and can be isolated in the non-metastatic early-stage cancer setting, and their associated miRNA profiles can potentially be utilized to predict treatment response.

Lacking Immunotherapy Biomarkers for Biliary Tract Cancer: A Comprehensive Systematic Literature Review and Meta-Analysis

BACKGROUND

Immunotherapy has recently been incorporated into the spectrum of biliary tract cancer (BTC) treatment. The identification of predictive response biomarkers is essential in order to identify those patients who may benefit most from this novel treatment option. Here, we propose a systematic literature review and a meta-analysis of PD-1, PD-L1, and other immune-related biomarker expression levels in patients with BTC.

METHODS

Prisma guidelines were followed for this systematic review and meta-analysis. Eligible studies were searched on PubMed. Studies published between 2017 and 2022, reporting data on PD-1/PD-L1 expression and other immune-related biomarkers in patients with BTC, were considered eligible.

RESULTS

A total of 61 eligible studies were identified. Despite the great heterogeneity between 39 studies reporting data on PD-L1 expression, we found a mean PD-L1 expression percentage (by choosing the lowest cut-off per study) of 25.6% (95% CI 21.0 to 30.3) in BTCs. The mean expression percentages of PD-L1 were 27.3%, 21.3%, and 27.4% in intrahepatic cholangiocarcinomas (iCCAs-15 studies), perihilar-distal CCAs (p/dCCAs-7 studies), and gallbladder cancer (GBC-5 studies), respectively. Furthermore, 4.6% (95% CI 2.38 to 6.97) and 2.5% (95% CI 1.75 to 3.34) of BTCs could be classified as TMB-H and MSI/MMRd tumors, respectively.

CONCLUSION

From our analysis, PD-L1 expression was found to occur approximately in 26% of BTC patients, with minimal differences based on anatomical location. TMB-H and MSI molecular phenotypes occurred less frequently. We still lack a reliable biomarker, especially in patients with mismatch-proficient tumors, and we must need to make an effort to conceive new prospective biomarker discovery studies.

A new, simple marker for predicting complicated appendicitis in patients with normal white blood cell count indicator; LUC

BACKGROUND

The aim of this study was to investigate the ability of a new marker that could be easily obtained to differentiate between complicated and uncomplicated appendicitis in a patients with a white blood cell (WBC) count within the normal range.

METHODS

The patients who underwent surgery with histopathologically proven acute appendicitis (AA) between January 2021 and October 2022 were evaluated retrospectively. Patients were classified into two groups as uncomplicated and complicated appendicitis, based on the surgical and histopathological findings. Groups were compared in terms of laboratory parameters at the time of hospital admission.

RESULTS

During the study period, 2589 patients underwent an appendectomy, among these 612 patients who had a WBC count within the normal range at the time of admission were analyzed. Uncomplicated appendicitis was detected in 79.6% of the patients and complicated appendicitis in 20.4%. Neutrophil%, neutrophil-to-lymphocyte ratio, C-reactive protein, and total bilirubin levels were significantly higher, whereas lymphocyte%, lymphocyte count, lymphocyte-to-monocyte ratio, sodium levels, and large unstained cells (LUC)% were significantly lower in patients with complicated appendicitis. Multiple logistic regression analysis revealed that lower LUC% (Odds Ratio [OR]: 0.45; 95% Confidence Intervals [CI]: 1.08-2.09; P=0.01) and higher total bilirubin levels (OR: 1.50; 95% CI: 1.08-2.09; P=0.01) were independent risk factors for complicated appendicitis.

CONCLUSION

In patients with a diagnosis of AA with a normal WBC value, LUC% obtained from the complete blood count can be used as a new parameter predicting the diagnosis of complicated appendicitis.

Pathologist-initiated reflex testing for biomarkers in non-small-cell lung cancer: expert consensus on the rationale and considerations for implementation

Biomarker tests in lung cancer have been traditionally ordered by the treating oncologist upon confirmation of an appropriate pathological diagnosis. The delay this introduces prolongs yet further what is already a complex, multi-stage, pre-treatment pathway and delays the start of first-line systemic treatment, which is crucially informed by the results of such analysis. Reflex testing, in which the responsibility for testing for an agreed range of biomarkers lies with the pathologist, has been shown to standardise and expedite the process. Twelve experts discussed the rationale and considerations for implementing reflex testing as standard clinical practice.

Biomarkers for Immune Checkpoint Inhibitor Response in NSCLC: Current Developments and Applicability

Lung cancer has the highest mortality rate among all cancer types, resulting in over 1.8 million deaths annually. Immunotherapy utilizing immune checkpoint inhibitors (ICIs) has revolutionized the treatment of non-small cell lung cancer (NSCLC). ICIs, predominantly monoclonal antibodies, modulate co-stimulatory and co-inhibitory signals crucial for maintaining immune tolerance. Despite significant therapeutic advancements in NSCLC, patients still face challenges such as disease progression, recurrence, and high mortality rates. Therefore, there is a need for predictive biomarkers that can guide lung cancer treatment strategies. Currently, programmed death-ligand 1 (PD-L1) expression is the only established biomarker for predicting ICI response. However, its accuracy and robustness are not consistently reliable. This review provides an overview of potential biomarkers currently under development or in the validation stage that hold promise in improving the classification of responders and non-responders to ICI therapy in the near future.

Neoadjuvant Immunotherapy: A Promising New Standard of Care

Neoadjuvant immunotherapy has emerged as a promising approach in the treatment of various malignancies, with preclinical studies showing improved immune responses in the preoperative setting. FDA-approved neoadjuvant-immunotherapy-based approaches include triple-negative breast cancer and early non-small cell lung cancer on the basis of improvement in pathological response and event free survival. Nevertheless, current trials have only shown benefits in a fraction of patients. It is therefore crucial to identify predictive biomarkers to improve patient selection for such approaches. This review aims to provide an overview of potential biomarkers of neoadjuvant immunotherapy in early triple-negative breast cancer, bladder cancer, melanoma, non-small cell lung cancer, colorectal cancer and gastric cancer. By the extrapolation of the metastatic setting, we explore known predictive biomarkers, i.e., PD-L1, mismatch repair deficiency and tumour mutational burden, as well as potential early-disease-specific biomarkers. We also discuss the challenges of identifying reliable biomarkers and the need for standardized protocols and guidelines for their validation and clinical implementation.

Tumor monocyte content predicts immunochemotherapy outcomes in esophageal adenocarcinoma

For inoperable esophageal adenocarcinoma (EAC), identifying patients likely to benefit from recently approved immunochemotherapy (ICI+CTX) treatments remains a key challenge. We address this using a uniquely designed window-of-opportunity trial (LUD2015-005), in which 35 inoperable EAC patients received first-line immune checkpoint inhibitors for four weeks (ICI-4W), followed by ICI+CTX. Comprehensive biomarker profiling, including generation of a 65,000-cell single-cell RNA-sequencing atlas of esophageal cancer, as well as multi-timepoint transcriptomic profiling of EAC during ICI-4W, reveals a novel T cell inflammation signature (INCITE) whose upregulation correlates with ICI-induced tumor shrinkage. Deconvolution of pre-treatment gastro-esophageal cancer transcriptomes using our single-cell atlas identifies high tumor monocyte content (TMC) as an unexpected ICI+CTX-specific predictor of greater overall survival (OS) in LUD2015-005 patients and of ICI response in prevalent gastric cancer subtypes from independent cohorts. Tumor mutational burden is an additional independent and additive predictor of LUD2015-005 OS. TMC can improve patient selection for emerging ICI+CTX therapies in gastro-esophageal cancer.

Tumor microenvironment in renal cell carcinoma: what is the current impact?

Tweetable abstract Tumor microenvironment plays a critical role in tumor progression and response to therapy. Recent studies show the potential of gene expression signatures and T cells to predict response to immunotherapy in renal cell carcinoma.

Ki67 proliferation index in follicular lymphoma is associated with favorable outcome in patients treated with R-CHOP

Follicular lymphoma (FL) is a common, indolent small B-cell lymphoma. While the Follicular Lymphoma International Prognostic Index is widely used, reliable prognostic and predictive biomarkers are needed. A recent study suggested that architectural patterns of CD10, BCL6, and Ki67 expression may correlate with progression-free survival (PFS) in FL patients treated with chemotherapy-free regimens. We examined the prognostic and predictive utility of architectural patterns of CD10, BCL6, Ki67, and FOXP1 in 90 patients treated with immunochemotherapy (bendamustine-rituximab [BR] and R-cyclophosphamide, doxorubicin, vincristine, prednisone [CHOP]). We found that high follicular Ki67 (≥30%) was associated with longer PFS in the subgroup of patients treated with R-CHOP but not among those treated with BR. Validation of this biomarker may support routine use of Ki67 as a predictive marker in FL.

Metastatic Castration-Resistant Prostate Cancer: Insights on Current Therapy and Promising Experimental Drugs

The therapeutic landscape of metastatic hormone sensitive and metastatic castration-resistant prostate cancer (mCRPC) is rapidly changing. We reviewed the current treatment options for mCRPC, with insights on new available therapeutic strategies. Chemotherapy with docetaxel or cabazitaxel (for patients progressing on docetaxel), as well as treatment with androgen receptor axis targeted therapies, and Radium-223 are well-established treatment options for patients with mCRPC. The advent of theragnostic in prostate cancer established Lutetium-177 (177Lu)-PSMA-617 as a new standard of care for PSMA-positive mCRPC previously treated with ARAT and taxane-based chemotherapy. Olaparib, a poly-ADP-ribose polymerase (PARP) inhibitor, is approved for selected patients with mCRPC progressed on ARATs and in combination with abiraterone acetate as first-line treatment for mCRPC. Immunotherapy showed limited efficacy in unselected patients with mCRPC and novel immunotherapy strategies need to be explored. The search for biomarkers is a growing field of interest in mCRPC, and predictive biomarkers are needed to support the choice of treatment and the development of tailored strategies.

Evaluating Targeted Therapeutic Response With Predictive Blood-Based Biomarkers in Patients With Chronic Mild Traumatic Brain Injury

Chronic consequences of mild traumatic brain injury (mTBI) are heterogeneous, but may be treatable with targeted medical and rehabilitation interventions. A biological signature for the likelihood of response to therapy (i.e., "predictive" biomarkers) would empower personalized medicine post-mTBI. The purpose of this study was to correlate pre-intervention blood biomarker levels and the likelihood of response to targeted interventions for patients with chronic issues attributable to mTBI. Patients with chronic symptoms and/or disorders secondary to mTBI >3 months previous (104 days to 15 years; n = 74) were enrolled. Participants completed pre-intervention assessments of symptom burden, comprehensive clinical evaluation, and blood-based biomarker measurements. Multi-domain targeted interventions for specific symptoms and impairments across a 6-month treatment period were prescribed. Participants completed a follow-up testing after the treatment period. An all-possible model's backward logistic regression was built to identify predictors of improvement in relation to blood biomarker levels before intervention. The minimum clinically important difference (MCID) of the change score (post-intervention subtracted from pre-intervention) for the Post-Concussion Symptom Scale (PCSS) to identify treatment responders from non-responders was the primary outcome. The MCID for total PCSS score was 10. The model to predict change in PCSS score over the 6-month intervention was significant (R² = 0.09; p = 0.01) and identified ubiquitin C-terminal hydrolase L1 (odds ratio [OR] = 2.53; 95% confidence interval [CI], 1.18-5.46; p = 0.02) and hyperphosphorylated tau (p-tau; OR = 0.70; 95% CI, 0.51-0.96; p = 0.03) as significant predictors of symptom improvement beyond the PCSS MCID. In this cohort of chronic TBI subjects, blood biomarkers before rehabilitation intervention predicted the likelihood of response to targeted therapy for chronic disorders post-TBI.

Treatment Refractoriness in Chronic Lymphocytic Leukemia: Old and New Molecular Biomarkers

Chronic lymphocytic leukemia (CLL) is the most common leukemia in adults. Despite its indolent clinical course, therapy refractoriness and disease progression still represent an unmet clinical need. Before the advent of pathway inhibitors, chemoimmunotherapy (CIT) was the commonest option for CLL treatment and is still widely used in areas with limited access to pathway inhibitors. Several biomarkers of refractoriness to CIT have been highlighted, including the unmutated status of immunoglobulin heavy chain variable genes and genetic lesions of TP53, BIRC3 and NOTCH1. In order to overcome resistance to CIT, targeted pathway inhibitors have become the standard of care for the treatment of CLL, with practice-changing results obtained through the inhibitors of Bruton tyrosine kinase (BTK) and BCL2. However, several acquired genetic lesions causing resistance to covalent and noncovalent BTK inhibitors have been reported, including point mutations of both BTK (e.g., C481S and L528W) and PLCG2 (e.g., R665W). Multiple mechanisms are involved in resistance to the BCL2 inhibitor venetoclax, including point mutations that impair drug binding, the upregulation of BCL2-related anti-apoptotic family members, and microenvironmental alterations. Recently, immune checkpoint inhibitors and CAR-T cells have been tested for CLL treatment, obtaining conflicting results. Potential refractoriness biomarkers to immunotherapy were identified, including abnormal levels of circulating IL-10 and IL-6 and the reduced presence of CD27⁺CD45RO^- CD8⁺ T cells.

Chasing Immune Checkpoint Inhibitors in Ovarian Cancer: Novel Combinations and Biomarker Discovery

A deep understanding of the tumor microenvironment and the recognition of tumor-infiltrating lymphocytes as a prognostic factor have resulted in major milestones in immunotherapy that have led to therapeutic advances in treating many cancers. Yet, the translation of this knowledge to clinical success for ovarian cancer remains a challenge. The efficacy of immune checkpoint inhibitors as single agents or combined with chemotherapy has been unsatisfactory, leading to the exploration of alternative combination strategies with targeted agents (e.g., poly-ADP-ribose inhibitors (PARP)and angiogenesis inhibitors) and novel immunotherapy approaches. Among the different histological subtypes, clear cell ovarian cancer has shown a higher sensitivity to immunotherapy. A deeper understanding of the mechanism of immune resistance within the context of ovarian cancer and the identification of predictive biomarkers remain central discovery benchmarks to be realized. This will be critical to successfully define the precision use of immune checkpoint inhibitors for the treatment of ovarian cancer.

Efficacy of Immune Checkpoint Blockade and Biomarkers of Response in Lymphoma: A Narrative Review

Immune checkpoint blockade (ICB) has revolutionized the prognosis of several advanced-stage solid tumors. However, its success has been far more limited in hematological malignancies and is mostly restricted to classical Hodgkin lymphoma (cHL) and primary mediastinal B cell lymphoma (PMBCL). In patients with non-Hodgkin lymphoma (NHL), response to PD-1/PD-L1 ICB monotherapy has been relatively limited, although some subtypes are more sensitive than others. Numerous predictive biomarkers have been investigated in solid malignancies, such as PD-L1 expression, tumor mutational burden (TMB) and microsatellite instability (MSI), among others. This review aims to appraise the current knowledge on PD-1/PD-L1 ICB efficacy in lymphoma when used either as monotherapy or combined with other agents, and describes potential biomarkers of response in this specific setting.

Targeting MET in Non-Small Cell Lung Cancer (NSCLC): A New Old Story?

In recent years, we have seen the development and approval for clinical use of an increasing number of therapeutic agents against actionable oncogenic drivers in metastatic non-small cell lung cancer (NSCLC). Among them, selective inhibitors, including tyrosine kinase inhibitors (TKIs) and monoclonal antibodies targeting the mesenchymal-epithelial transition (MET) receptor, have been studied in patients with advanced NSCLC with MET deregulation, primarily due to exon 14 skipping mutations or MET amplification. Some MET TKIs, including capmatinib and tepotinib, have proven to be highly effective in this molecularly defined subgroup of patients and are already approved for clinical use. Other similar agents are being tested in early-stage clinical trials with promising antitumor activity. The purpose of this review is to provide an overview of MET signaling pathways, MET oncogenic alterations primarily focusing on exon 14 skipping mutations, and the laboratory techniques used to detect MET alterations. Furthermore, we will summarize the currently available clinical data and ongoing studies on MET inhibitors, as well as the mechanisms of resistance to MET TKIs and new potential strategies, including combinatorial approaches, to improve the clinical outcomes of MET exon 14-altered NSCLC patients.

Predictive Biomarkers of Pathological Response to Neoadjuvant Chemoradiotherapy for Locally Advanced Soft Tissue Sarcomas

BACKGROUND

Marginally resectable and unresectable soft tissue sarcomas (STS) remain a therapy challenge due to the lack of highly active treatment. The aim of the study was to identify a biomarker to predict the pathological response (PR) to preplanned treatment of these STSs.

METHODS

In the phase II clinical trial (NCT03651375), locally advanced STS patients received preoperative treatment with a combination of doxorubicin-ifosfamide chemotherapy and 5 × 5 Gy radiotherapy. PR to the treatment was classified using the European Organization for Research and Treatment of Cancer-Soft Tissue and Bone Sarcoma Group recommendations. We have chosen HIF-1α, CD163, CD68, CD34, CD105, and γH2AFX proteins, rendering different biological phenomena, for biomarker study.

RESULTS

Nineteen patients were enrolled and in four cases a good PR was reported. The high expression of HIF-1α before surgery showed a negative correlation with PR, which means a poor response to therapy. Furthermore, the samples after surgery had decreased expression of HIF-1α, which confirmed the correlation with PR. However, high expression of γH2AFX positively correlated with PR, which provides better PR. The high number of positive-staining TAMs and the high IMVD did not correlate with PR.

CONCLUSIONS

HIF1α and γH2AFX could be potential biomarkers for PR prediction after neoadjuvant treatment in STS.

Hope and Hype around Immunotherapy in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) holds a poor prognosis compared to other breast cancer subtypes, and the development of new effective treatment strategies is an unmet medical need. TNBC has traditionally been considered not amenable to treatment with targeted agents due to a lack of actionable targets. Therefore, chemotherapy has remained the mainstay of systemic treatment for many decades. The advent of immunotherapy raised very hopeful expectations in TNBC, possibly due to higher levels of tumor-infiltrating lymphocytes, PD-L1 expression and tumor mutational burden compared to other breast cancer subtypes, that predict an effective anti-tumor immune-engagement. The results of clinical trials testing immunotherapy in TNBC led to the approval of the combination of immune checkpoint inhibitors and chemotherapy in both early and advanced settings. However, some open questions about the use of immunotherapy in TNBC still exist. These include a deeper understanding of the heterogeneity of the disease, identification of reliable predictive biomarkers of response, determination of the most appropriate chemotherapy backbone and appropriate management of potential long-term immune-related adverse events. In this review we aim to examine the available evidence on the use of immunotherapy strategies in both early and advanced TNBC, to critically discuss some of the limitations encountered in clinical research and to summarize data on novel promising immunotherapeutic strategies beyond PD-(L)1 blockade that have been investigated in the most recent trials.

Exploratory Genome-Wide Association Analysis to Identify Pharmacogenetic Determinants of Response to R-CHOP in Diffuse Large B-Cell Lymphoma

R-CHOP standard chemotherapy is successful in about 60% of diffuse large B-cell lymphoma (DLBCL) patients. Unresponsive patients have a poor prognosis, and predictive biomarkers of response to R-CHOP are lacking. We conducted the first prospective GWAS study aimed at exploring constitutional biomarkers predictive of R-CHOP efficacy and toxicity. Overall, 216 any-stage chemonaïve DLBCL patients candidate to R-CHOP were enrolled. The median age of the 185 eligible patients was 59.2 years, 49.7% were women and 45.4% were stage I-II patients. According to the Revised International Prognostic Index (R-IPI), 14.1%, 56.8% and 29.2% were in the very good, good and poor prognosis groups, respectively. Of the patients, 85.9% produced a complete response. Highly significant associations (i.e., p < 5 × 10^-8) were found between progression-free survival (PFS) and six SNPs (i.e., rs116665727, rs1607795, rs75614943, rs77241831, rs117500207, rs78466241). Additionally, five SNPs (i.e., rs74832512, rs117500207, rs35789195, rs11721010, rs12356569) were highly associated with overall survival (OS). Wild-type patients showed a prolonged PFS or OS compared with patients carrying deleterious alleles (p < 0.001). No association with the adequate significant threshold was observed between SNPs and the objective response or toxicity. In the future, these SNPs, alone or in combination, after a proper validation in an independent cohort, could contribute to improving the prediction of R-CHOP response.

Development of a Prediction Model for Short-Term Remission of Patients with Crohn's Disease Treated with Anti-TNF Drugs

Therapy with anti-tumor necrosis factor (TNF) has dramatically changed the natural history of Crohn's disease (CD). However, these drugs are not without adverse events, and up to 40% of patients could lose efficacy in the long term. We aimed to identify reliable markers of response to anti-TNF drugs in patients with CD. A consecutive cohort of 113 anti-TNF naive patients with CD was stratified according to clinical response as short-term remission (STR) or non-STR (NSTR) at 12 weeks of treatment. We compared the protein expression profiles of plasma samples in a subset of patients from both groups prior to anti-TNF therapy by SWATH proteomics. We identified 18 differentially expressed proteins (p ≤ 0.01, fold change ≥ 2.4) involved in the organization of the cytoskeleton and cell junction, hemostasis/platelet function, carbohydrate metabolism, and immune response as candidate biomarkers of STR. Among them, vinculin was one of the most deregulated proteins (p < 0.001), whose differential expression was confirmed by ELISA (p = 0.054). In the multivariate analysis, plasma vinculin levels along with basal CD Activity Index, corticosteroids induction, and bowel resection were factors predicting NSTR.