Proportional Hazards Violations in Phase 3 Cancer Clinical Trials: A Potential Source of Trial Misinterpretation.

BACKGROUND: Survival analyses of novel agents with long-term responders often exhibit differential hazard rates over time. Such proportional hazards violations (PHVs) may reduce the power of the log-rank test and lead to misinterpretation of trial results. We aimed to characterize the incidence and study attributes associated with PHVs in phase 3 oncology trials and assess the utility of restricted mean survival time (RMST) and MaxCombo as additional analyses. METHODS: Clinicaltrials.gov and PubMed were searched to identify 2-arm, randomized, phase 3 superiority-design cancer trials with time-to-event primary endpoints and published results through 2020. Patient-level data were reconstructed from published Kaplan-Meier curves. PHVs were assessed using Schoenfeld residuals. RESULTS: Three hundred fifty-seven Kaplan-Meier comparisons across 341 trials were analyzed, encompassing 292,831 enrolled patients. PHVs were identified in 85/357 (23.8%; 95%CI 19.7%, 28.5%) comparisons. In multivariable analysis, non-OS endpoints (odds ratio [OR] 2.16 [95%CI 1.21, 3.87]; P=.009) were associated with higher odds of PHVs, and immunotherapy comparisons (OR 1.94 [95%CI 0.98, 3.86]; P=.058) were weakly suggestive of higher odds of PHVs. Few trials with PHVs (25/85, 29.4%) pre-specified a statistical plan to account for PHVs. Fourteen trials with PHVs exhibited discordant statistical signals with RMST or MaxCombo, of which ten (71%) reported negative results. CONCLUSION: PHVs are common across therapy types, and attempts to account for PHVs in statistical design are lacking despite the potential for results exhibiting non-proportional hazards to be misinterpreted.

REDOMA: Bayesian random-effects dose-optimization meta-analysis using spike-and-slab priors.

The rise of cutting-edge precision cancer treatments has led to a growing significance of the optimal biological dose (OBD) in modern oncology trials. These trials now prioritize the consideration of both toxicity and efficacy simultaneously when determining the most desirable dosage for treatment. Traditional approaches in early-phase oncology trials have conventionally relied on the assumption of a monotone relationship between treatment efficacy and dosage. However, this assumption may not hold valid for novel oncology therapies. In reality, the dose-efficacy curve of such treatments may reach a plateau at a specific dose, posing challenges for conventional methods in accurately identifying the OBD. Furthermore, achieving reliable identification of the OBD is typically not possible based on a single small-sample trial. With data from multiple phase I and phase I/II trials, we propose a novel Bayesian random-effects dose-optimization meta-analysis (REDOMA) approach to identify the OBD by synthesizing toxicity and efficacy data from each trial. The REDOMA method can address trials with heterogeneous characteristics. We adopt a curve-free approach based on a Gamma process prior to model the average dose-toxicity relationship. In addition, we utilize a Bayesian model selection framework that uses the spike-and-slab prior as an automatic variable selection technique to eliminate monotonic constraints on the dose-efficacy curve. The good performance of the REDOMA method is confirmed by extensive simulation studies.

Joint multi-omics discriminant analysis with consistent representation learning using PANDA.

Integrative multi-omics analysis provides deeper insight and enables better and more realistic modeling of the underlying biology and causes of diseases than does single omics analysis. Although several integrative multi-omics analysis methods have been proposed and demonstrated promising results in integrating distinct omics datasets, inconsistent distribution of the different omics data, which is caused by technology variations, poses a challenge for paired integrative multi-omics methods. In addition, the existing discriminant analysis-based integrative methods do not effectively exploit correlation and consistent discriminant structures, necessitating a compromise between correlation and discrimination in using these methods. Herein we present PAN-omics Discriminant Analysis (PANDA), a joint discriminant analysis method that seeks omics-specific discriminant common spaces by jointly learning consistent discriminant latent representations for each omics. PANDA jointly maximizes between-class and minimizes within-class omics variations in a common space and simultaneously models the relationships among omics at the consistency representation and cross-omics correlation levels, overcoming the need for compromise between discrimination and correlation as with the existing integrative multi-omics methods. Because of the consistency representation learning incorporated into the objective function of PANDA, this method seeks a common discriminant space to minimize the differences in distributions among omics, can lead to a more robust latent representations than other methods, and is against the inconsistency of the different omics. We compared PANDA to 10 other state-of-the-art multi-omics data integration methods using both simulated and real-world multi-omics datasets and found that PANDA consistently outperformed them while providing meaningful discriminant latent representations. PANDA is implemented using both R and MATLAB, with codes available at https://github.com/WuLabMDA/PANDA.

Case report: Molecular profiling facilitates the diagnosis of a challenging case of lung cancer with choriocarcinoma features.

Accurate diagnoses are crucial in determining the most effective treatment across different cancers. In challenging cases, morphology-based traditional pathology methods have important limitations, while molecular profiling can provide valuable information to guide clinical decisions. We present a 35-year female with lung cancer with choriocarcinoma features. Her disease involved the right lower lung, brain, and thoracic lymph nodes. The pathology from brain metastasis was reported as "metastatic choriocarcinoma" (a germ cell tumor) by local pathologists. She initiated carboplatin and etoposide, a regimen for choriocarcinoma. Subsequently, her case was assessed by pathologists from an academic cancer center, who gave the diagnosis of "adenocarcinoma with aberrant expression of ß-hCG" and finally pathologists at our hospital, who gave the diagnosis of "poorly differentiated carcinoma with choriocarcinoma features". Genomic profiling detected a KRAS G13R mutation and transcriptomics profiling was suggestive of lung origin. The patient was treated with carboplatin/paclitaxel/ipilimumab/nivolumab followed by consolidation radiation therapy. She had no evidence of progression to date, 16 months after the initial presentation. The molecular profiling could facilitate diagnosing of challenging cancer cases. In addition, chemoimmunotherapy and local consolidation radiation therapy may provide promising therapeutic options for patients with lung cancer exhibiting choriocarcinoma features.

Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights.

While we recognize the prognostic importance of clinicopathological measures and circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers to prognosis in non-small cell lung cancer (NSCLC) remains underexplored. In our multi-institutional study of 394 NSCLC patients, we utilize pre-treatment computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to establish a habitat imaging framework for assessing regional heterogeneity within individual tumors. This framework identifies three PET/CT subtypes, which maintain prognostic value after adjusting for clinicopathologic risk factors including tumor volume. Additionally, these subtypes complement ctDNA in predicting disease recurrence. Radiogenomics analysis unveil the molecular underpinnings of these imaging subtypes, highlighting downregulation in interferon alpha and gamma pathways in the high-risk subtype. In summary, our study demonstrates that these habitat imaging subtypes effectively stratify NSCLC patients based on their risk levels for disease recurrence after initial curative surgery or radiotherapy, providing valuable insights for personalized treatment approaches.

Synthetic PET from CT improves diagnosis and prognosis for lung cancer: Proof of concept.

[18F]Fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) are indispensable components in modern medicine. Although PET can provide additional diagnostic value, it is costly and not universally accessible, particularly in low-income countries. To bridge this gap, we have developed a conditional generative adversarial network pipeline that can produce FDG-PET from diagnostic CT scans based on multi-center multi-modal lung cancer datasets (n = 1,478). Synthetic PET images are validated across imaging, biological, and clinical aspects. Radiologists confirm comparable imaging quality and tumor contrast between synthetic and actual PET scans. Radiogenomics analysis further proves that the dysregulated cancer hallmark pathways of synthetic PET are consistent with actual PET. We also demonstrate the clinical values of synthetic PET in improving lung cancer diagnosis, staging, risk prediction, and prognosis. Taken together, this proof-of-concept study testifies to the feasibility of applying deep learning to obtain high-fidelity PET translated from CT.

Clinical Benefit from Docetaxel +/- Ramucirumab Is Not Associated with Mutation Status in Metastatic Non-Small-Cell Lung Cancer Patients Who Progressed on Platinum Doublets and Immunotherapy.

Docetaxel +/- ramucirumab remains the standard-of-care therapy for patients with metastatic non-small-cell lung cancer (NSCLC) after progression on platinum doublets and immune checkpoint inhibitors (ICIs). The aim of our study was to investigate whether the cancer gene mutation status was associated with clinical benefits from docetaxel +/- ramucirumab. We also investigated whether platinum/taxane-based regimens offered a better clinical benefit in this patient population. A total of 454 patients were analyzed (docetaxel +/- ramucirumab n=381; platinum/taxane-based regimens n=73). Progression-free survival (PFS) and overall survival (OS) were compared among different subpopulations with different cancer gene mutations and between patients who received docetaxel +/- ramucirumab versus platinum/taxane-based regimens. Among patients who received docetaxel +/- ramucirumab, the top mutated cancer genes included TP53 (n=167), KRAS (n=127), EGFR (n=65), STK11 (n=32), ERBB2 (HER2) (n=26), etc. None of these cancer gene mutations or PD-L1 expression was associated with PFS or OS. Platinum/taxane-based regimens were associated with a significantly longer mQS (13.00 m, 95% Cl: 11.20-14.80 m versus 8.40 m, 95% Cl: 7.12-9.68 m, LogRank P=0.019) than docetaxel +/- ramcirumab. Key prognostic factors including age, histology, and performance status were not different between these two groups. In conclusion, in patients with metastatic NSCLC who have progressed on platinum doublets and ICIs, the clinical benefit from docetaxel +/- ramucirumab is not associated with the cancer gene mutation status. Platinum/taxane-based regimens may offer a superior clinical benefit over docetaxel +/- ramucirumab in this patient population.

Association of differential censoring with survival and suboptimal control arms among oncology clinical trials.

Differential censoring, which refers to censoring imbalance between treatment arms, may bias the interpretation of survival outcomes in clinical trials. In 146 phase III oncology trials with statistically significant time-to-event surrogate primary endpoints, we evaluated the association between differential censoring in the surrogate primary endpoints, control arm adequacy, and the subsequent statistical significance of overall survival results. Twenty-four (16%) trials exhibited differential censoring that favored the control arm, whereas 15 (10%) exhibited differential censoring that favored the experimental arm. Positive overall survival was more common in control arm differential censoring trials (63%) than in trials without differential censoring (37%) or with experimental arm differential censoring (47%; odds ratio = 2.64, 95% confidence interval = 1.10 to 7.20; P = .04). Control arm differential censoring trials more frequently used suboptimal control arms at 46% compared with 20% without differential censoring and 13% with experimental arm differential censoring (odds ratio = 3.60, 95% confidence interval = 1.29 to 10.0; P = .007). The presence of control arm differential censoring in trials with surrogate primary endpoints, especially in those with overall survival conversion, may indicate an inadequate control arm and should be examined and explained.

Revisiting Feeding Tube Utilization in Oropharynx Cancer: 6-Year Prospective Registry Analysis.

OBJECTIVE: Patients treated for oropharyngeal cancer (OPC) have historically demonstrated high feeding tube rates for decreased oral intake and malnutrition. We re-examined feeding tube practices in these patients. STUDY DESIGN: Retrospective analysis of prospective cohort from 2015 to 2021. SETTING: Single-institution NCI-Designated Comprehensive Cancer Center. METHODS: With IRB approval, patients with new oropharyngeal squamous cell cancer or (unknown primary with neck metastasis) were enrolled. Baseline swallowing was assessed via videofluoroscopy and Performance Status Scale for Head and Neck Cancer (PSSHN). G-tubes or nasogastric tubes (NGT) were placed for weight loss before, during, or after treatment. Prophylactic NGT were placed during transoral robotic surgery (TORS). Tube duration was censored at last disease-free follow-up. Multivariate regression was performed for G-tube placement (odds ratio [OR] [95% confidence interval [CI]) and removal (Cox hazard ratio, hazard ratio [HR] [95% CI]). RESULTS: Of 924 patients, most had stage I to II (81%), p16+ (89%), node-positive (88%) disease. Median follow-up was 2.6 years (interquartile range 1.5-3.9). Most (91%) received radiation/chemoradiation, and 16% received TORS. G-tube rate was 27% (5% after TORS). G-tube risk was increased with chemoradiation (OR 2.78 [1.87-4.22]) and decreased with TORS (OR 0.31 [0.15-0.57]) and PSSHN-Diet score ≥60 (OR 0.26 [0.15-0.45]). G-tube removal probability over time was lower for T3 to T4 tumors (HR 0.52 [0.38-0.71]) and higher for PSSHN-Diet score ≥60 (HR 1.65 [1.03-2.66]). CONCLUSIONS: In this modern cohort of patients treated for OPC, 27% received G-tubes-50% less than institutional rates 10 years ago. Patients with preserved baseline swallowing and/or those eligible for TORS may have lower G-tube risk and duration.

Multi-omics Analysis Reveals Immune Features Associated with Immunotherapy Benefit in Patients with Squamous Cell Lung Cancer from Phase III Lung-MAP S1400I Trial.

PURPOSE: Identifying molecular and immune features to guide immune checkpoint inhibitor (ICI)-based regimens remains an unmet clinical need. EXPERIMENTAL DESIGN: Tissue and longitudinal blood specimens from phase III trial S1400I in patients with metastatic squamous non-small cell carcinoma (SqNSCLC) treated with nivolumab monotherapy (nivo) or nivolumab plus ipilimumab (nivo+ipi) were subjected to multi-omics analyses including multiplex immunofluorescence (mIF), nCounter PanCancer Immune Profiling Panel, whole-exome sequencing, and Olink. RESULTS: Higher immune scores from immune gene expression profiling or immune cell infiltration by mIF were associated with response to ICIs and improved survival, except regulatory T cells, which were associated with worse overall survival (OS) for patients receiving nivo+ipi. Immune cell density and closer proximity of CD8+GZB+ T cells to malignant cells were associated with superior progression-free survival and OS. The cold immune landscape of NSCLC was associated with a higher level of chromosomal copy-number variation (CNV) burden. Patients with LRP1B-mutant tumors had a shorter survival than patients with LRP1B-wild-type tumors. Olink assays revealed soluble proteins such as LAMP3 increased in responders while IL6 and CXCL13 increased in nonresponders. Upregulation of serum CXCL13, MMP12, CSF-1, and IL8 were associated with worse survival before radiologic progression. CONCLUSIONS: The frequency, distribution, and clustering of immune cells relative to malignant ones can impact ICI efficacy in patients with SqNSCLC. High CNV burden may contribute to the cold immune microenvironment. Soluble inflammation/immune-related proteins in the blood have the potential to monitor therapeutic benefit from ICI treatment in patients with SqNSCLC.

Pathologic Processing of Lung Cancer Resection Specimens After Neoadjuvant Therapy.

Neoadjuvant treatment of non-small cell lung cancer challenges the traditional processing of pathology specimens. Induction therapy before resection allows evaluation of the efficacy of neoadjuvant agents at the time of surgery. Many clinical trials use pathologic tumor response, measured as major pathologic response (MPR, ≤10% residual viable tumor [RVT]) or complete pathologic response (CPR, 0% RVT) as a surrogate of clinical efficacy. Consequently, accurate pathologic evaluation of RVT is crucial. However, pathologic assessment has not been uniform, which is particularly true for sampling of the primary tumor, which instead of the traditional processing, requires different tissue submission because the focus has shifted from tumor typing alone to RVT scoring. Using a simulation study, we analyzed the accuracy rates of %RVT, MPR, and CPR of 31 pretreated primary lung tumors using traditional grossing compared with the gold standard of submitting the entire residual primary tumor and identified the minimum number of tumor sections to be submitted to ensure the most accurate scoring of %RVT, MPR, and CPR. Accurate %RVT, MPR, and CPR calls were achieved in 52%, 87%, and 81% of cases, respectively, using the traditional grossing method. Accuracy rates of at least 90% for these parameters require either submission of all residual primary tumor or at least 20 tumor sections. Accurate %RVT, MPR, and CPR scores cannot be achieved with traditional tumor grossing. Submission of the entire primary tumor, up to a maximum of 20 sections, is required for the most accurate reads.

Surgical outcomes after chemotherapy plus nivolumab and chemotherapy plus nivolumab and ipilimumab in patients with non-small cell lung cancer.

OBJECTIVE: Chemotherapy plus nivolumab is the standard of care neoadjuvant treatment for patients with resectable stage IB to IIIA non-small cell lung cancer. The influence of dual checkpoint blockade with chemotherapy on surgical outcomes remains unknown. We aimed to determine operative complexity and perioperative outcomes associated with neoadjuvant chemotherapy and nivolumab with or without ipilimumab. METHODS: A total of 44 patients with stage IB (≥4 cm) to IIIA non-small cell lung cancer were treated on sequential platform arms of the NEOSTAR trial. A total of 22 patients were treated with nivolumab + chemotherapy, and 22 patients were treated with ipilimumab + nivolumab + chemotherapy. The safety of surgical resection after neoadjuvant therapy was estimated using 30-day complication rates. Operative reports and surgeons' narratives were evaluated to determine procedural complexity and operative conduct. RESULTS: All 22 of 22 patients (100%) treated with nivolumab + chemotherapy underwent surgical resection: 20 R0 (90.9%), 17 (77.3%) lobectomies, 1 wedge resection, 2 segmentectomies, and 2 pneumonectomies. The majority, 21 of 22 (95%), were performed by thoracotomy. A total of 13 of 22 (59.1%) were rated as challenging resections. A total of 4 of 22 patients (18.2%) experienced grade 3 or greater Clavien-Dindo complication. A total of 20 of 22 patients (90.9%) treated with ipilimumab + nivolumab + chemotherapy underwent surgical resection: 19 R0 (95%), 18 (90%) lobectomies, 1 pneumonectomy, and 1 segmentectomy. A total of 16 of 20 (80%) resections were performed via thoracotomy, 3 of 20 (15%) via robotics, and 1 of 20 (5%) via thoracoscopy. A total of 9 of 20 (45%) resections were considered challenging. A total of 4 of 20 patients (20%) experienced grade 3 or greater Clavien-Dindo complication. CONCLUSIONS: Surgical resections are feasible and safe, with high rates of R0 after neoadjuvant chemotherapy and nivolumab with or without ipilimumab. Overall, approximately half of cases (22/42, 52.3%) were considered to be more challenging than a standard lobectomy.

Real-World Efficacy and Safety of Amivantamab for EGFR-Mutant NSCLC.

INTRODUCTION: Amivantamab-vmjw (amivantamab) is a bispecific EGFR/MET antibody approved for patients with advanced NSCLC with EGFR exon 20 insertion mutations, after prior therapy. Nevertheless, the benefits and safety of amivantamab in other EGFR-mutant lung cancer, with or without osimertinib, and with concurrent radiation therapy, are less known. METHODS: We queried the MD Anderson Lung Cancer GEMINI, Fred Hutchinson Cancer Research Center, University of California Davis Comprehensive Cancer Center, and Stanford Cancer Center's database for patients with EGFR-mutant NSCLC treated with amivantamab, not on a clinical trial. The data analyzed included initial response, duration of treatment, and concomitant radiation safety in overall population and prespecified subgroups. RESULTS: A total of 61 patients received amivantamab. Median age was 65 (31-81) years old; 72.1% were female; and 77% were patients with never smoking history. Median number of prior lines of therapies was four. On the basis of tumor's EGFR mutation, 39 patients were in the classical mutation cohort, 15 patients in the exon 20 cohort, and seven patients in the atypical cohort. There were 37 patients (58.7%) who received amivantamab concomitantly with osimertinib and 25 patients (39.1%) who received concomitant radiation. Furthermore, 54 patients were assessable for response in the overall population; 19 patients (45.2%) had clinical response and disease control rate (DCR) was 64.3%. In the classical mutation cohort of the 33 assessable patients, 12 (36.4%) had clinical response and DCR was 48.5%. In the atypical mutation cohort, six of the seven patients (85.7%) had clinical response and DCR was 100%. Of the 13 assessable patients in the exon 20 cohort, five patients (35.7%) had clinical response and DCR was 64.3%. Adverse events reported with amivantamab use were similar as previously described in product labeling. No additional toxicities were noted when amivantamab was given with radiation with or without osimertinib. CONCLUSIONS: Our real-world multicenter analysis revealed that amivantamab is a potentially effective treatment option for patients with EGFR mutations outside of exon 20 insertion mutations. The combination of osimertinib with amivantamab is safe and feasible. Radiation therapy also seems safe when administered sequentially or concurrently with amivantamab.

Distinct patterns of auto-reactive antibodies associated with organ-specific immune-related adverse events.

The roles of preexisting auto-reactive antibodies in immune-related adverse events (irAEs) associated with immune checkpoint inhibitor therapy are not well defined. Here, we analyzed plasma samples longitudinally collected at predefined time points and at the time of irAEs from 58 patients with immunotherapy naïve metastatic non-small cell lung cancer treated on clinical protocol with ipilimumab and nivolumab. We used a proteomic microarray system capable of assaying antibody reactivity for IgG and IgM fractions against 120 antigens for systemically evaluating the correlations between auto-reactive antibodies and certain organ-specific irAEs. We found that distinct patterns of auto-reactive antibodies at baseline were associated with the subsequent development of organ-specific irAEs. Notably, ACHRG IgM was associated with pneumonitis, anti-cytokeratin 19 IgM with dermatitis, and anti-thyroglobulin IgG with hepatitis. These antibodies merit further investigation as potential biomarkers for identifying high-risk populations for irAEs and/or monitoring irAEs during immunotherapy treatment. Trial registration: ClinicalTrials.gov identifier: NCT03391869.

A novel Bayesian model for assessing intratumor heterogeneity of tumor infiltrating leukocytes with multi-region gene expression sequencing.

Intratumor heterogeneity (ITH) of tumor-infiltrated leukocytes (TILs) is an important phenomenon of cancer biology with potentially profound clinical impacts. Multi-region gene expression sequencing data provide a promising opportunity that allows for explorations of TILs and their intratumor heterogeneity for each subject. Although several existing methods are available to infer the proportions of TILs, considerable methodological gaps exist for evaluating intratumor heterogeneity of TILs with multi-region gene expression data. Here, we develop ICeITH, immune cell estimation reveals intratumor heterogeneity, a Bayesian hierarchical model that borrows cell type profiles as prior knowledge to decompose mixed bulk data while accounting for the within-subject correlations among tumor samples. ICeITH quantifies intratumor heterogeneity by the variability of targeted cellular compositions. Through extensive simulation studies, we demonstrate that ICeITH is more accurate in measuring relative cellular abundance and evaluating intratumor heterogeneity compared with existing methods. We also assess the ability of ICeITH to stratify patients by their intratumor heterogeneity score and associate the estimations with the survival outcomes. Finally, we apply ICeITH to two multi-region gene expression datasets from lung cancer studies to classify patients into different risk groups according to the ITH estimations of targeted TILs that shape either pro- or anti-tumor processes. In conclusion, ICeITH is a useful tool to evaluate intratumor heterogeneity of TILs from multi-region gene expression data.

REAP-2: An interactive quantitative tool for robust and efficient dose-response curve estimation.

REAP-2 is an interactive dose-response curve estimation tool for Robust and Efficient Assessment of drug Potency. It provides user-friendly dose-response curve estimation for in vitro studies and conducts statistical testing for model comparisons with a redesigned user interface. We also make a major update of the underlying estimation method with penalized beta regression, which demonstrates great reliability and accuracy in dose estimation and uncertainty quantification. In this note, we describe the method and implementation of REAP-2 with a highlight on potency estimation and drug comparison.

Pathomic Features Reveal Immune and Molecular Evolution From Lung Preneoplasia to Invasive Adenocarcinoma.

Recent statistics on lung cancer, including the steady decline of advanced diseases and the dramatically increasing detection of early-stage diseases and indeterminate pulmonary nodules, mark the significance of a comprehensive understanding of early lung carcinogenesis. Lung adenocarcinoma (ADC) is the most common histologic subtype of lung cancer, and atypical adenomatous hyperplasia is the only recognized preneoplasia to ADC, which may progress to adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) and eventually to invasive ADC. Although molecular evolution during early lung carcinogenesis has been explored in recent years, the progress has been significantly hindered, largely due to insufficient materials from ADC precursors. Here, we employed state-of-the-art deep learning and artificial intelligence techniques to robustly segment and recognize cells on routinely used hematoxylin and eosin histopathology images and extracted 9 biology-relevant pathomic features to decode lung preneoplasia evolution. We analyzed 3 distinct cohorts (Japan, China, and United States) covering 98 patients, 162 slides, and 669 regions of interest, including 143 normal, 129 atypical adenomatous hyperplasia, 94 AIS, 98 MIA, and 205 ADC. Extracted pathomic features revealed progressive increase of atypical epithelial cells and progressive decrease of lymphocytic cells from normal to AAH, AIS, MIA, and ADC, consistent with the results from tissue-consuming and expensive molecular/immune profiling. Furthermore, pathomics analysis manifested progressively increasing cellular intratumor heterogeneity along with the evolution from normal lung to invasive ADC. These findings demonstrated the feasibility and substantial potential of pathomics in studying lung cancer carcinogenesis directly from the low-cost routine hematoxylin and eosin staining.

ATM Mutations Associate with Distinct Co-Mutational Patterns and Therapeutic Vulnerabilities in NSCLC.

PURPOSE: Ataxia-telangiectasia mutated (ATM) is the most frequently mutated DNA damage repair gene in non-small cell lung cancer (NSCLC). However, the molecular correlates of ATM mutations and their clinical implications have not been fully elucidated. EXPERIMENTAL DESIGN: Clinicopathologic and genomic data from 26,587 patients with NSCLC from MD Anderson, public databases, and a de-identified nationwide (US-based) NSCLC clinicogenomic database (CGDB) were used to assess the co-mutation landscape, protein expression, and mutational processes in ATM-mutant tumors. We used the CGDB to evaluate ATM-associated outcomes in patients treated with immune checkpoint inhibitors (ICI) with or without chemotherapy, and assessed the effect of ATM loss on STING signaling and chemotherapy sensitivity in preclinical models. RESULTS: Nonsynonymous mutations in ATM were observed in 11.2% of samples (2,980/26,587) and were significantly associated with mutations in KRAS, but mutually exclusive with EGFR (q < 0.1). KRAS mutational status constrained the ATM co-mutation landscape, with strong mutual exclusivity with TP53 and KEAP1 within KRAS-mutated samples. Those ATM mutations that co-occurred with TP53 were more likely to be missense mutations and associate with high mutational burden, suggestive of non-functional passenger mutations. In the CGDB cohort, dysfunctional ATM mutations associated with improved OS only in patients treated with ICI-chemotherapy, and not ICI alone. In vitro analyses demonstrated enhanced upregulation of STING signaling in ATM knockout cells with the addition of chemotherapy. CONCLUSIONS: ATM mutations define a distinct subset of NSCLC associated with KRAS mutations, increased TMB, decreased TP53 and EGFR co-occurrence, and potential increased sensitivity to ICIs in the context of DNA-damaging chemotherapy.

International Association for the Study of Lung Cancer Study of Reproducibility in Assessment of Pathologic Response in Resected Lung Cancers After Neoadjuvant Therapy.

INTRODUCTION: Pathologic response has been proposed as an early clinical trial end point of survival after neoadjuvant treatment in clinical trials of NSCLC. The International Association for the Study of Lung Cancer (IASLC) published recommendations for pathologic evaluation of resected lung cancers after neoadjuvant therapy. The aim of this study was to assess pathologic response interobserver reproducibility using IASLC criteria. METHODS: An international panel of 11 pulmonary pathologists reviewed hematoxylin and eosin-stained slides from the lung tumors of resected NSCLC from 84 patients who received neoadjuvant immune checkpoint inhibitors in six clinical trials. Pathologic response was assessed for percent viable tumor, necrosis, and stroma. For each slide, tumor bed area was measured microscopically, and pre-embedded formulas calculated unweighted and weighted major pathologic response (MPR) averages to reflect variable tumor bed proportion. RESULTS: Unanimous agreement among pathologists for MPR was observed in 68 patients (81%), and inter-rater agreement (IRA) was 0.84 (95% confidence interval [CI]: 0.76-0.92) and 0.86 (95% CI: 0.79-0.93) for unweighted and weighted averages, respectively. Overall, unweighted and weighted methods did not reveal significant differences in the classification of MPR. The highest concordance by both methods was observed for cases with more than 95% viable tumor (IRA = 0.98, 95% CI: 0.96-1) and 0% viable tumor (IRA = 0.94, 95% CI: 0.89-0.98). The most common reasons for discrepancies included interpretations of tumor bed, presence of prominent stromal inflammation, distinction between reactive and neoplastic pneumocytes, and assessment of invasive mucinous adenocarcinoma. CONCLUSIONS: Our study revealed excellent reliability in cases with no residual viable tumor and good reliability for MPR with the IASLC recommended less than or equal to 10% cutoff for viable tumor after neoadjuvant therapy.

SwarmDeepSurv: swarm intelligence advances deep survival network for prognostic radiomics signatures in four solid cancers.

Survival models exist to study relationships between biomarkers and treatment effects. Deep learning-powered survival models supersede the classical Cox proportional hazards (CoxPH) model, but substantial performance drops were observed on high-dimensional features because of irrelevant/redundant information. To fill this gap, we proposed SwarmDeepSurv by integrating swarm intelligence algorithms with the deep survival model. Furthermore, four objective functions were designed to optimize prognostic prediction while regularizing selected feature numbers. When testing on multicenter sets (n = 1,058) of four different cancer types, SwarmDeepSurv was less prone to overfitting and achieved optimal patient risk stratification compared with popular survival modeling algorithms. Strikingly, SwarmDeepSurv selected different features compared with classical feature selection algorithms, including the least absolute shrinkage and selection operator (LASSO), with nearly no feature overlapping across these models. Taken together, SwarmDeepSurv offers an alternative approach to model relationships between radiomics features and survival endpoints, which can further extend to study other input data types including genomics.