Emerging advances in defining the molecular and therapeutic landscape of small-cell lung cancer.

Small-cell lung cancer (SCLC) has traditionally been considered a recalcitrant cancer with a dismal prognosis, with only modest advances in therapeutic strategies over the past several decades. Comprehensive genomic assessments of SCLC have revealed that most of these tumours harbour deletions of the tumour-suppressor genes TP53 and RB1 but, in contrast to non-small-cell lung cancer, have failed to identify targetable alterations. The expression status of four transcription factors with key roles in SCLC pathogenesis defines distinct molecular subtypes of the disease, potentially enabling specific therapeutic approaches. Overexpression and amplification of MYC paralogues also affect the biology and therapeutic vulnerabilities of SCLC. Several other attractive targets have emerged in the past few years, including inhibitors of DNA-damage-response pathways, epigenetic modifiers, antibody-drug conjugates and chimeric antigen receptor T cells. However, the rapid development of therapeutic resistance and lack of biomarkers for effective selection of patients with SCLC are ongoing challenges. Emerging single-cell RNA sequencing data are providing insights into the plasticity and intratumoural and intertumoural heterogeneity of SCLC that might be associated with therapeutic resistance. In this Review, we provide a comprehensive overview of the latest advances in genomic and transcriptomic characterization of SCLC with a particular focus on opportunities for translation into new therapeutic approaches to improve patient outcomes.

A matching-based machine learning approach to estimating optimal dynamic treatment regimes with time-to-event outcomes.

Observational data (e.g. electronic health records) has become increasingly important in evidence-based research on dynamic treatment regimes, which tailor treatments over time to patients based on their characteristics and evolving clinical history. It is of great interest for clinicians and statisticians to identify an optimal dynamic treatment regime that can produce the best expected clinical outcome for each individual and thus maximize the treatment benefit over the population. Observational data impose various challenges for using statistical tools to estimate optimal dynamic treatment regimes. Notably, the task becomes more sophisticated when the clinical outcome of primary interest is time-to-event. Here, we propose a matching-based machine learning method to identify the optimal dynamic treatment regime with time-to-event outcomes subject to right-censoring using electronic health record data. In contrast to the established inverse probability weighting-based dynamic treatment regime methods, our proposed approach provides better protection against model misspecification and extreme weights in the context of treatment sequences, effectively addressing a prevalent challenge in the longitudinal analysis of electronic health record data. In simulations, the proposed method demonstrates robust performance across a range of scenarios. In addition, we illustrate the method with an application to estimate optimal dynamic treatment regimes for patients with advanced non-small cell lung cancer using a real-world, nationwide electronic health record database from Flatiron Health.

Sotorasib with panitumumab in chemotherapy-refractory KRASG12C-mutated colorectal cancer: a phase 1b trial.

The current third-line (and beyond) treatment options for RAS-mutant metastatic colorectal cancer have yielded limited efficacy. At the time of study start, the combination of sotorasib, a KRAS (Kirsten rat sarcoma viral oncogene homolog)-G12C inhibitor, and panitumumab, an epidermal growth factor receptor (EGFR) inhibitor, was hypothesized to overcome treatment-induced resistance. This phase 1b substudy of the CodeBreaK 101 master protocol evaluated sotorasib plus panitumumab in patients with chemotherapy-refractory KRASG12C-mutated metastatic colorectal cancer. Here, we report the results in a dose-exploration cohort and a dose-expansion cohort. Patients received sotorasib (960 mg, once daily) plus panitumumab (6 mg kg-1, once every 2 weeks). The primary endpoints were safety and tolerability. Secondary endpoints included efficacy and pharmacokinetics. Exploratory biomarkers at baseline were assessed. Forty-eight patients (dose-exploration cohort, n = 8; dose-expansion cohort, n = 40) were treated. Treatment-related adverse events of any grade and grade ≥3 occurred in 45 (94%) and 13 (27%) patients, respectively. In the dose-expansion cohort, the confirmed objective response rate was 30.0% (95% confidence interval (CI) 16.6%, 46.5%). Median progression-free survival was 5.7 months (95% CI 4.2, 7.7 months). Median overall survival was 15.2 months (95% CI 12.5 months, not estimable). Prevalent genomic coalterations included APC (84%), TP53 (74%), SMAD4 (33%), PIK3CA (28%) and EGFR (26%). Sotorasib-panitumumab demonstrated acceptable safety with promising efficacy in chemotherapy-refractory KRASG12C-mutated metastatic colorectal cancer. ClinicalTrials.gov identifier: NCT04185883 .

Keeping a track on leptomeningeal disease in non-small cell lung cancer: A single-institution experience with CNSideTM.

Background: Leptomeningeal disease (LMD) is a devastating complication for patients with advanced cancer. Diagnosis and monitoring the response to therapy remains challenging due to limited sensitivity and specificity of standard-of-care (SOC) diagnostic modalities, including cerebrospinal fluid (CSF) cytology, MRI, and clinical evaluation. These hindrances contribute to the poor survival of LMD patients. CNSide is a CLIA-validated test that detects and characterizes CSF-derived tumor cells and cell-free (cf) DNA. We performed a retrospective analysis on the utility of CNSide to analyze CSF obtained from advanced non-small cell lung cancer (aNSCLC) patients with suspected LMD treated at the Huntsman Cancer Institute in Salt Lake City, UT. Methods: CNSide was used to evaluate CSF from 15 patients with aNSCLC. CSF tumor cell quantification was performed throughout treatment for 5 patients. CSF tumor cells and cfDNA were characterized for actionable mutations. Results: In LMD-positive patients, CNSide detected CSF tumor cells in 88% (22/25) samples versus 40% (10/25) for cytology (matched samples). CSF tumor cell numbers tracked response to therapy in 5 patients where CNSide was used to quantify tumor cells throughout treatment. In 75% (9/12) of the patients, genetic alterations were detected in CSF, with the majority representing gene mutations and amplifications with therapeutic potential. The median survival for LMD patients was 16.1 m (5.2-NR). Conclusions: We show that CNSide can supplement the management of LMD in conjunction with SOC methods for the diagnosis, monitoring response to therapy, and identifying actionable mutations unique to the CSF in patients with LMD.

Disparities in outcomes between Black and White patients in North America with thoracic malignancies and COVID-19 infection (TERAVOLT).

BACKGROUND: Patients with thoracic malignancies who develop COVID-19 infection have a higher hospitalization rate compared to the general population and to those with other cancer types, but how this outcome differs by race and ethnicity is relatively understudied. METHODS: The TERAVOLT database is an international, multi-center repository of cross-sectional and longitudinal data studying the impact of COVID-19 on individuals with thoracic malignancies. Patients from North America with thoracic malignancies and confirmed COVID-19 infection were included for this analysis of racial and ethnic disparities. Patients with missing race data or races and ethnicities with fewer than 50 patients were excluded from analysis. Multivariable analyses for endpoints of hospitalization and death were performed on these 471 patients. RESULTS: Of the 471 patients, 73% were White and 27% were Black. The majority (90%) were non-Hispanic ethnicity, 5% were Hispanic, and 4% were missing ethnicity data. Black patients were more likely to have an Eastern Cooperative Oncology Group (ECOG) Performance Status ≥ 2 (p-value = 0.04). On multivariable analysis, Black patients were more likely than White patients to require hospitalization (Odds Ratio (OR): 1.69, 95% CI: 1.01-2.83, p-value = 0.044). These differences remained across different waves of the pandemic. However, no statistically significant difference in mortality was found between Black and White patients (OR 1.29, 95% CI: 0.69-2.40, p-value = 0.408). CONCLUSIONS: Black patients with thoracic malignancies who acquire COVID-19 infection are at a significantly higher risk of hospitalization compared to White patients, but there is no significant difference in mortality. The underlying drivers of racial disparity among patients with thoracic malignancies and COVID-19 infection require ongoing investigation.

Real-world pan-cancer landscape of frameshift mutations and their role in predicting responses to immune checkpoint inhibitors in cancers with low tumor mutational burden.

BACKGROUND: Pembrolizumab is FDA approved for tumors with tumor mutational burden (TMB) of ≥10 mutations/megabase (mut/Mb). However, the response to immune checkpoint inhibitors (ICI) varies significantly among cancer histologies. We describe the landscape of frameshift mutations (FSs) and evaluated their role as a predictive biomarker to ICI in a clinical cohort of patients. METHODS: Comprehensive genomic profiling was performed on a cohort of solid tumor samples examining at least 324 genes. The clinical cohort included patients with metastatic solid malignancies who received ICI monotherapy and had tumor sequencing. Progression-free survival (PFS), overall survival, and objective response rates (ORR) were compared between the groups. RESULTS: We analyzed 246,252 microsatellite stable (MSS) and 4561 samples with microsatellite instability across solid tumors. Histologies were divided into groups according to TMB and FS. MSS distribution: TMB-L (<10 mut/Mb)/FS-A (absent FS) (N=111,065, 45%), TMB-H (≥10 mut/Mb)/FS-A (N=15,313, 6%), TMB-L/FS-P (present ≥1 FS) (N=98,389, 40%) and TMB-H/FS-P (N=21,485, 9%). FSs were predominantly identified in the p53 pathway. In the clinical cohort, 212 patients were included. Groups: TMB-L/FS-A (N=80, 38%), TMB-H/FS-A (N=36, 17%), TMB-L/FS-P (N=57, 27%), TMB-H/FS-P (N=39, 18%). FSs were associated with a higher ORR to ICI, 23.8% vs 12.8% (p=0.02). TMB-L/FS-P had superior median PFS (5.1 months) vs TMB-L/FS-A (3.6 months, p<0.01). The 12-month PFS probability was 34% for TMB-L/FS-P vs 17.1% for TMB-L/FS-A. CONCLUSIONS: FSs are found in 47% of patients with MSS/TMB-L solid tumors in a pan-cancer cohort. FS may complement TMB in predicting immunotherapy responses, particularly for tumors with low TMB.

Phase II Randomized Trial of Carboplatin, Pemetrexed, and Bevacizumab With and Without Atezolizumab in Stage IV Nonsquamous Non-Small-Cell Lung Cancer Patients Who Harbor a Sensitizing EGFR Mutation or Have Never Smoked.

INTRODUCTION: Patients with non-small-cell lung cancer (NSCLC) who have never smoked or have tumors with mutations in EGFR generally derive minimal benefit from single-agent PD-1/PD-L1 checkpoint inhibitors. Prior data indicate that adding PD-L1 inhibition to anti-VEGF and cytotoxic chemotherapy may be a promising approach to overcoming immunotherapy resistance in these patients, however prospective validation is needed. This trial in progress (NCT03786692) is evaluating patients with stage IV NSCLC who have never smoked or who have tumors with sensitizing EGFR alterations to determine if a 4-drug combination of atezolizumab, carboplatin, pemetrexed, and bevacizumab can improve outcomes compared to carboplatin, pemetrexed and bevacizumab without atezolizumab. METHODS: This is a randomized, phase II, multicenter study evaluating carboplatin, pemetrexed, bevacizumab with and without atezolizumab in 117 patients with stage IV nonsquamous NSCLC. Randomization is 2 to 1 favoring the atezolizumab containing arm. Eligible patients include: 1) those with tumors with sensitizing EGFR alterations in exons 19 or 21 or 2) patients who have never smoked and have wild-type tumors (ie, no EGFR, ALK or ROS1 alterations). Patients are defined as having never smoked if they have smoked less than 100 cigarettes in a lifetime. Patients with EGFR-mutated tumors must have disease progression or intolerance to prior tyrosine kinase inhibitor (TKI) therapy. The primary endpoint is progression-free survival (PFS). Secondary endpoints include overall survival (OS), response rate, duration of response, and time to response. CONCLUSION: This phase II trial is accruing patients at U.S. sites through the National Comprehensive Cancer Network (NCCN). The trial opened in August 2019 and accrual is expected to be completed in the Fall of 2024.

A rare FGF5 candidate variant (rs112475347) for predisposition to nonsquamous, nonsmall-cell lung cancer.

A unique approach with rare resources was used to identify candidate variants predisposing to familial nonsquamous nonsmall-cell lung cancers (NSNSCLC). We analyzed sequence data from NSNSCLC-affected cousin pairs belonging to high-risk lung cancer pedigrees identified in a genealogy of Utah linked to statewide cancer records to identify rare, shared candidate predisposition variants. Variants were tested for association with lung cancer risk in UK Biobank. Evidence for linkage with lung cancer was also reviewed in families from the Genetic Epidemiology of Lung Cancer Consortium. Protein prediction modeling compared the mutation with reference. We sequenced NSNSCLC-affected cousin pairs from eight high-risk lung cancer pedigrees and identified 66 rare candidate variants shared in the cousin pairs. One variant in the FGF5 gene also showed significant association with lung cancer in UKBiobank. This variant was observed in 3/163 additional sampled Utah lung cancer cases, 2 of whom were related in another independent pedigree. Modeling of the predicted protein predicted a second binding site for SO4 that may indicate binding differences. This unique study identified multiple candidate predisposition variants for NSNSCLC, including a rare variant in FGF5 that was significantly associated with lung cancer risk and that segregated with lung cancer in the two pedigrees in which it was observed. FGF5 is an oncogenic factor in several human cancers, and the mutation found here (W81C) changes the binding ability of heparan sulfate to FGF5, which might lead to its deregulation. These results support FGF5 as a potential NSNSCLC predisposition gene and present additional candidate predisposition variants.

Real-world comparison of survival outcomes with cisplatin versus carboplatin in patients with limited-stage small-cell lung cancer.

INTRODUCTION: Limited-stage small-cell lung cancer (LS-SCLC) is potentially curable with concurrent chemoradiation (CRT). Cisplatin is the preferred platinum for the chemotherapy backbone in national guidelines. Unfortunately, many LS-SCLC patients are elderly, with comorbidities and poor performance status (PS), which preclude the use of cisplatin. Carboplatin may be a suitable alternative. This analysis evaluates the overall survival (OS) and time to next treatment (TTNT) in LS-SCLC patients receiving concurrent CRT by platinum use. MATERIALS AND METHODS: The study included LS-SCLC patients in the Flatiron Health nationwide de-identified electronic health record-derived database who received CRT in 2013-2019 with follow-up through May 2020. TTNT and OS were compared using both unadjusted and inverse propensity-weighted Cox proportional hazards models. RESULTS: This study included patients treated with carboplatin (n = 600) or cisplatin (n = 572) in combination with etoposide and radiation. Cisplatin patients were younger, had a shorter time from diagnosis to radiation, and had less kidney disease. In an unadjusted analysis, median overall survival (mOS) was greater in the cisplatin group than the carboplatin group with mOS of 22.3 months vs. 19.2 months and Hazard Ratio (HR) of 0.83 (p = 0.01). In the inverse propensity-weighted analysis, this difference was no longer significant (HR 0.93, p = 0.37). No differences were seen in TTNT. CONCLUSION: When balancing on key clinical factors, we observed no statistical difference in OS or TTNT by platinum choice in real-world LS-SCLC patients treated with CRT.  Although observational, the results from this large data set are consistent with the hypothesis that either cisplatin or carboplatin is an appropriate therapy regardless of health status.

A Real-World Analysis of the Use of Systemic Therapy in Malignant Pleural Mesothelioma and the Differential Impacts on Overall Survival by Practice Pattern.

INTRODUCTION: Malignant pleural mesothelioma (MPM) is an aggressive malignancy that affects older adults with frequent comorbidities, making real-world treatment decisions challenging. This study compares the overall survival (OS) of patients with MPM by physician's choice of first-line (1L) platinum chemotherapy (PC), second-line (2L) immunotherapy versus chemotherapy, and by receipt of maintenance therapy (MT). METHODS: The study included patients diagnosed with advanced MPM in the Flatiron Health electronic health record-derived database who initiated PC with pemetrexed in the 1L setting between 2011 and 2019. Patients in the 2L therapy analysis received single-agent chemotherapy versus immunotherapy after the progression of disease from our 1L cohort. Patients in the MT cohort were identified on the basis of continued receipt of pemetrexed with or without bevacizumab after dropping PC at prespecified intervals. The OS of patients by choice of 1L PC, 2L immunotherapy versus chemotherapy, and receipt of MT was summarized by means of Kaplan-Meier survival estimates and compared in the context of propensity score matching weighted analyses. RESULTS: In propensity score matching weighting analysis from 2065 patients with MPM, there was no evidence of an OS difference by choice of 1L PC (hazard ratio [HR] = 1.08, 95% confidence interval [CI]: 0.89-1.31, p = 0.43), suggestive evidence of an OS difference by choice of 2L immunotherapy versus chemotherapy (HR = 0.68, 95% CI: 0.42-1.08; p = 0.10), and no evidence of an OS difference by receipt of MT (HR = 0.92, 95% CI: 0.72-1.16, p = 0.46). CONCLUSIONS: Using real-world, propensity score-matched weighted analysis of MPM, we found there was no difference in OS by choice of 1L PC, 2L immunotherapy or chemotherapy, or by receipt of MT.

A Definitive Prognostication System for Patients With Thoracic Malignancies Diagnosed With Coronavirus Disease 2019: An Update From the TERAVOLT Registry.

INTRODUCTION: Patients with thoracic malignancies are at increased risk for mortality from coronavirus disease 2019 (COVID-19), and a large number of intertwined prognostic variables have been identified so far. METHODS: Capitalizing data from the Thoracic Cancers International COVID-19 Collaboration (TERAVOLT) registry, a global study created with the aim of describing the impact of COVID-19 in patients with thoracic malignancies, we used a clustering approach, a fast-backward step-down selection procedure, and a tree-based model to screen and optimize a broad panel of demographics and clinical COVID-19 and cancer characteristics. RESULTS: As of April 15, 2021, a total of 1491 consecutive eligible patients from 18 countries were included in the analysis. With a mean observation period of 42 days, 361 events were reported with an all-cause case fatality rate of 24.2%. The clustering procedure screened 73 covariates in 13 clusters. A further multivariable logistic regression for the association between clusters and death was performed, resulting in five clusters significantly associated with the outcome. The fast-backward step-down selection procedure then identified the following seven major determinants of death: Eastern Cooperative Oncology Group-performance status (ECOG-PS) (OR = 2.47, 1.87-3.26), neutrophil count (OR = 2.46, 1.76-3.44), serum procalcitonin (OR = 2.37, 1.64-3.43), development of pneumonia (OR = 1.95, 1.48-2.58), C-reactive protein (OR = 1.90, 1.43-2.51), tumor stage at COVID-19 diagnosis (OR = 1.97, 1.46-2.66), and age (OR = 1.71, 1.29-2.26). The receiver operating characteristic analysis for death of the selected model confirmed its diagnostic ability (area under the receiver operating curve = 0.78, 95% confidence interval: 0.75-0.81). The nomogram was able to classify the COVID-19 mortality in an interval ranging from 8% to 90%, and the tree-based model recognized ECOG-PS, neutrophil count, and c-reactive protein as the major determinants of prognosis. CONCLUSIONS: From 73 variables analyzed, seven major determinants of death have been identified. Poor ECOG-PS was found to have the strongest association with poor outcome from COVID-19. With our analysis, we provide clinicians with a definitive prognostication system to help determine the risk of mortality for patients with thoracic malignancies and COVID-19.

Dynamic Prediction of Near-Term Overall Survival in Patients with Advanced NSCLC Based on Real-World Data.

Patients with terminal cancers commonly receive aggressive and sub-optimal treatment near the end of life, which may not be beneficial in terms of duration or quality of life. To improve end-of-life care, it is essential to develop methods that can accurately predict the short-term risk of death. However, most prediction models for patients with cancer are static in the sense that they only use patient features at a fixed time. We proposed a dynamic prediction model (DPM) that can incorporate time-dependent predictors. We apply this method to patients with advanced non-small-cell lung cancer from a real-world database. Inverse probability of censoring weighted AUC with bootstrap inference was used to compare predictions among models. We found that increasing ECOG performance status and decreasing albumin had negative prognostic associations with overall survival (OS). Moreover, the negative prognostic implications strengthened over the patient disease course. DPMs using both time-independent and time-dependent predictors substantially improved short-term prediction accuracy compared to Cox models using only predictors at a fixed time. The proposed model can be broadly applied for prediction based on longitudinal data, including an estimation of the dynamic effects of time-dependent features on OS and updating predictions at any follow-up time.

Systemic and Radiation Therapy Approaches for Locally Advanced Non-Small-Cell Lung Cancer.

The treatment for locally advanced non-small-cell lung cancer has changed dramatically over the past several years, with consolidative immunotherapy after concurrent chemoradiation becoming the new standard of care. Five-year survival outcomes have substantially improved with this approach. Despite these advances, further improvements are needed as the majority of patients ultimately develop progression of disease. The next-generation immunotherapy trials are currently being conducted that include approaches such as concurrent immunotherapy and addition of other therapeutic agents in the concurrent and consolidative settings. Specific unmet needs continue to exist for patients who develop disease progression after concurrent chemoradiation and immunotherapy, as well as defining the best treatment for patients with driver mutations. Future directions also include refinement of radiation techniques to reduce toxicities as much as possible, as well as the use of circulating tumor DNA in the surveillance setting. The current scientific landscape shows promising approaches that may further improve outcomes for patients with locally advanced non-small-cell lung cancer.

Role of CTLA Inhibition in Management of Non-Small Cell Lung Cancer.

PURPOSE OF REVIEW: The use of single-agent or combination immunotherapy strategies has revolutionized the management of patients with non-small cell lung cancer (NSCLC). Here, we review the current role for CTLA-4 inhibitors in early-stage resectable NSCLC, unresectable stage III NSCLC, and in metastatic NSCLC. RECENT FINDINGS: Immunotherapy agents alone, or in combination with chemotherapy, represent the new standard of care for the management of metastatic squamous and non-squamous NSCLC without driver mutations. Combination CTLA-4 and PD-1/L1 inhibitors can be efficacious, particularly in tumor mutation burden (TMB) high tumors, providing a chemotherapy-free strategy for metastatic patients. Early signals from neoadjuvant trials suggest a benefit for combination CTLA-4 and PD-1 inhibitions prior to surgery, with improved rates of major pathologic response (MPR). The role for CTLA4 inhibitors is currently unknown in the adjuvant and unresectable stage III setting, although clinical trials are ongoing to evaluate this approach. There is a growing role for CTLA-4 inhibition in the neoadjuvant and metastatic settings for patients with NSCLC. Biomarker selection in ongoing clinical trials will be crucial to guide patient selection for CTLA4 inhibitor therapy. Combination strategies with PD-1/L1 inhibition have demonstrated the greatest efficacy to date.

Small Cell Lung Cancer, Version 2.2022, NCCN Clinical Practice Guidelines in Oncology.

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Small Cell Lung Cancer (SCLC) provide recommended management for patients with SCLC, including diagnosis, primary treatment, surveillance for relapse, and subsequent treatment. This selection for the journal focuses on metastatic (known as extensive-stage) SCLC, which is more common than limited-stage SCLC. Systemic therapy alone can palliate symptoms and prolong survival in most patients with extensive-stage disease. Smoking cessation counseling and intervention should be strongly promoted in patients with SCLC and other high-grade neuroendocrine carcinomas. The "Summary of the Guidelines Updates" section in the SCLC algorithm outlines the most recent revisions for the 2022 update, which are described in greater detail in this revised Discussion text.

Molecular characterization of Kita-Kyushu lung cancer antigen (KK-LC-1) expressing carcinomas.

Cancer/testis antigens (CTAs) are strongly expressed in some solid tumors but minimally expressed in normal tissue, making them appealing therapeutic targets. KK-LC-1 (CXorf61) has cytoplasmic expression in gastric, breast, and lung cancer. We characterized the molecular subtypes of non-small cell lung cancer (NSCLC) expressing KK-LC-1 to inform rational clinical trials of T-cell receptor therapy (TCR-T) targeting KK-LC-1. 9790 NSCLC tumors that underwent whole transcriptome sequencing (Illumina NovaSeq) and NextGen DNA sequencing (NextSeq, 592 Genes and NovaSEQ, WES) at Caris Life Sciences (Phoenix, AZ) were analyzed. Tumors were split into quartiles based on KK-LC-1 expression and pathological and molecular differences were investigated. Adenocarcinoma had significantly higher KK-LC-1 expression than squamous cell carcinoma (median, 3.25 vs. 1.17 transcripts per million (TPM), p < 0.0001). Tumors with the highest quartile of KK-LC-1 expression had a greater proportion of tumors with high tumor mutation burden (TMB) (≥10 mutations per megabase; 44% vs. 28% in Q1, p < 0.001). Increased KK-LC-1 expression was associated with increased M1 macrophage abundance. Higher levels of KK-LC-1 expression were seen in pan-wild type and KRAS mutated tumors and associated with high TMB. TCR-T therapy directed against KK-LC-1 should be considered in patients whose clinical features reflect these characteristics.

Impact of XPO1 mutations on survival outcomes in metastatic non-small cell lung cancer (NSCLC).

BACKGROUND: Nuclear protein transport is essential in guiding the traffic of important proteins and RNAs between the nucleus and cytoplasm. Export of proteins from the nucleus is mostly regulated by Exportin 1 (XPO1). In cancer, XPO1 is almost universally hyperactive and can promote the export of important tumor suppressors to the cytoplasm. Currently, there are no studies evaluating XPO1 amplifications and mutations in NSCLC and the impact on outcomes. METHODS: Tumor samples were analyzed using next-generation sequencing (NGS) (NextSeq, 592 Genes), immunohistochemistry (IHC), and whole transcriptome sequencing (WTS, NovaSeq) (Caris Life Sciences, Phoenix, AZ). Survival was extracted from insurance claims data and calculated from time of tissue collection to last contact using Kaplan-Meier estimate. RESULTS: Among 18,218 NSCLC tumors sequenced, 26 harbored XPO1 mutations and 24 had amplifications. XPO1 mutant tumors were more likely to have high TMB (79% vs. 52%, p = 0.007) and less likely to have high PD-L1 (32% vs. 68%, p = 0.03). KRAS co-mutations were seen in 19% (n = 5) and EGFR co-mutations were rare (n = 2). Among the 17,449 NSCLC tumors with clinical data, there were 24 XPO1 mutant. Comparison of survival between XPO1 mutant and WT showed a negative association with a hazard ratio (HR) of 1.932 (95% CI: 1.144-3.264 p = 0.012). XPO1 amplification was not associated with survival. CONCLUSIONS: XPO1 pathogenic mutations were associated with a poor survival in NSCLC. Although XPO1 mutations are rare in NSCLC, further studies to assess its associations with treatment responses are warranted.

The role of gut microbiome in modulating response to immune checkpoint inhibitor therapy in cancer.

Immunotherapy has led to a paradigm shift in the treatment of several cancers. There have been significant efforts to identify biomarkers that can predict response and toxicities related to immune checkpoint inhibitor (ICPI) therapy. Despite these advances, it has been challenging to tease out why a subset of patients benefit more than others or why certain patients experience immune-related adverse events (irAEs). Although the immune-modulating properties of the human gut bacterial ecosystem are yet to be fully elucidated, there has been growing interest in evaluating the role of the gut microbiome in shaping the therapeutic response to cancer immunotherapy. Considerable research efforts are currently directed to utilizing metagenomic and metabolic profiling of stool microbiota in patients on ICPI-based therapies. Dysbiosis or loss of microbial diversity has been associated with a poor treatment response to ICPIs and worse survival outcomes in cancer patients. Emerging data have shown that certain bacterial strains, such as Faecalibacterium that confer sensitivity to ICPI, also have a higher propensity to increase the risk of irAEs. Additionally, the microbiome can modulate the local immune response at the intestinal interface and influence the trafficking of bacterial peptide primed T-cells distally, influencing the toxicity patterns to ICPI. Antibiotic or diet induced alterations in composition of the microbiome can also indirectly alter the production of certain bacterial metabolites such as deoxycholate and short chain fatty acids that can influence the anti-tumor tolerogenesis. Gaining sufficient understanding of the exact mechanisms underpinning the interplay between ICPI induced anti-tumor immunity and the immune modulatory role gut microbiome can be vital in identifying potential avenues of improving outcomes to cancer immunotherapy. In the current review, we have summarized and highlighted the key emerging data supporting the role of gut microbiome in regulating response to ICPIs in cancer.