HLA diversity unveils susceptibility and organ-specific occurrence of second primary cancers: a prospective cohort study.

BACKGROUND: Up to 17% of cancer survivors have been reported to develop second primary cancers (SPC), which cause significant physical and economic distress and often complicate clinical decision-making. However, understanding of SPC remains limited and superficial. Human leukocyte antigen (HLA) is characterized by its polymorphism and has been associated with various diseases. This study aims to explore the role of HLA diversity in SPC incidence. METHODS: We analyzed a cohort of 47,550 cancer patients from the UK Biobank. SNP-derived HLA alleles were used and SPC-related HLA alleles were identified using logistic regression, followed by stepwise filtering based on the Akaike information criterion (AIC) and permutation tests. Additionally, we examined the association between extragenetic factors and the risk of SPC in patients carrying hazardous HLA alleles. RESULTS: During a median follow-up of 3.11 years, a total of 2894 (6.09%) participants developed SPC. We identified three protective HLA alleles (DRB1*04:03 and DPA1*02:02 for males and DRB5*01:01 for females) and two hazardous alleles (A*26:01 for males and DPB1*11:01 for females) about SPC. The presence of the protective alleles was associated with a reduced SPC risk (males: hazard ratio [HR] 0.72, 95% confidence interval [CI] 0.59-0.89; females: HR 0.81, 95% CI 0.70-0.93), while the hazardous alleles were linked to an increased risk (males: HR 1.27, 95% CI 1.03-1.56; females: HR 1.35, 95% CI 1.07-1.70). The hazardous allele A*26:01 indicated skin-lung organ-specific SPC occurrence in males. Animal fat and vitamin C were associated with SPC risk in males carrying the hazardous alleles, while free sugar and vegetable fat were linked to SPC risk in females. CONCLUSIONS: These results suggest that HLA alleles may serve as biomarkers for the susceptibility and organ-specific occurrence of SPC, while dietary modulation may mitigate hazardous alleles-related SPC risk, potentially aiding in the early prediction and prevention of SPC.

Bi-phase CT radiomics nomogram for the preoperative prediction of pylorus lymph node metastasis in non-pyloric gastric cancer patients.

BACKGROUND: The expansion of function-preserving surgery became possible due to a more profound understanding of gastric cancer (GC), and T1N + or T2N + gastric cancer patients might be potential beneficiaries. However, ways to evaluate the possibility of function-preserving pylorus surgery are still unknown. METHODS: A total of 288 patients at Renji Hospital and 58 patients at Huadong Hospital, pathologically diagnosed with gastric cancer staging at T1 and T2 with tumors located in the upper two-thirds of the stomach, were retrospectively enrolled from March 2015 to October 2022. Tumor regions of interest (ROIs) were manually delineated on bi-phase CT images, and a nomogram was built and evaluated. RESULTS: The radiomic features distributed differently between positive and negative pLNm groups. Two radiomic signatures (RS1 and RS2) and one clinical signature were constructed. The radiomic signatures exhibited good performance for discriminating pLNm status in the test set. The three signatures were then combined into an integrated nomogram (IN). The IN showed good discrimination of pLNm in the Renji cohort (AUC 0.918) and the Huadong cohort (AUC 0.649). The verification models showed high values. CONCLUSION: For GC patients with T1 and T2 tumors located in the upper two-thirds of the stomach, a nomogram was successfully built for predicting pylorus lymph node metastasis, which would guide the surgical indication extension of conservative gastrectomies.

Regular Use of Aspirin and Statins Reduces the Risk of Cancer in Individuals with Systemic Inflammatory Diseases.

Aspirin has shown potential for cancer prevention, but a recent large randomized controlled trial found no evidence for a reduction in cancer risk. Given the anti-inflammatory effects of aspirin, systemic inflammatory diseases (SID), such as osteoporosis, cardiovascular diseases, and metabolic diseases, could potentially modify the aspirin-cancer link. To investigate the impact of aspirin in people with SIDs, we conducted an observational study on a prospective cohort of 478,615 UK Biobank participants. Individuals with at least one of the 41 SIDs displayed a higher cancer risk than those without SIDs. Regular aspirin use showed protective effects exclusively in patients with SID, contrasting an elevated risk among their non-SID counterparts. Nonetheless, aspirin use demonstrated preventative potential only for 9 of 21 SID-associated cancer subtypes. Cholesterol emerged as another key mediator linking SIDs to cancer risk. Notably, regular statin use displayed protective properties in patients with SID but not in their non-SID counterparts. Concurrent use of aspirin and statins exhibited a stronger protective association in patients with SID, covering 14 common cancer subtypes. In summary, patients with SIDs may represent a population particularly responsive to regular aspirin and statin use. Promoting either combined or individual use of these medications within the context of SIDs could offer a promising chemoprevention strategy. SIGNIFICANCE: Individuals with systemic inflammatory diseases derive chemoprotective benefits from aspirin and statins, providing a precision cancer prevention approach to address the personal and public challenges posed by cancer.

CDK4/6 inhibition triggers ICAM1-driven immune response and sensitizes LKB1 mutant lung cancer to immunotherapy.

Liver kinase B1 (LKB1) mutation is prevalent and a driver of resistance to immune checkpoint blockade (ICB) therapy for lung adenocarcinoma. Here leveraging single cell RNA sequencing data, we demonstrate that trafficking and adhesion process of activated T cells are defected in genetically engineered Kras-driven mouse model with Lkb1 conditional knockout. LKB1 mutant cancer cells result in marked suppression of intercellular adhesion molecule-1 (ICAM1). Ectopic expression of Icam1 in Lkb1-deficient tumor increases homing and activation of adoptively transferred SIINFEKL-specific CD8+ T cells, reactivates tumor-effector cell interactions and re-sensitises tumors to ICB. Further discovery proves that CDK4/6 inhibitors upregulate ICAM1 transcription by inhibiting phosphorylation of retinoblastoma protein RB in LKB1 deficient cancer cells. Finally, a tailored combination strategy using CDK4/6 inhibitors and anti-PD-1 antibodies promotes ICAM1-triggered immune response in multiple Lkb1-deficient murine models. Our findings renovate that ICAM1 on tumor cells orchestrates anti-tumor immune response, especially for adaptive immunity.

Interstitial pneumonitis associated with combined regimen of immunotherapy and conventional therapies-pharmacovigilance database analysis with real-world data validation.

BACKGROUND: Immune checkpoint inhibitor (ICI) therapy combined with conventional therapies is being broadly applied in non-small cell lung cancer (NSCLC) patients. However, the risk of interstitial pneumonitis (IP) following a combined regimen is incompletely characterized. METHODS: A total of 46,127 NSCLC patients were extracted for disproportionality analyses of IP from the Food and Drug Administration's Adverse Event Reporting System (FAERS) database. A total of 1108 NSCLC patients who received ICI treatment at Nanfang Hospital of Southern Medical University were collected and utilized for real-world validation. RESULTS: Of the 46,127 patients with NSCLC, 3830 cases (8.3%; 95% confidence interval [CI], 8.05-8.56) developed IP. Multivariable logistic regression analyses revealed that the adjusted ROR of ICI combined with radiation (RT) was the highest (121.69; 95% CI, 83.60-184.96; P < 0.0001) among all therapies, while that of ICI combined with chemotherapy (CHEMO) or targeted therapy (TARGET) was 0.90 (95% CI, 0.78-1.04; P = 0.160) and 1.49 (95% CI, 0.95-2.23; P = 0.065), respectively, using ICI monotherapy as reference. Furthermore, analyses from our validation cohort of 1108 cases showed that the adjusted odds ratio of ICI combined with RT was the highest (12.25; 95% CI, 3.34-50.22; P < 0.01) among all the therapies, while that of ICI combined with CHEMO or TARGET was 2.32 (95% CI, 0.89-7.92; P = 0.12) and 0.66 (95% CI, 0.03-4.55; P = 0.71), respectively, using ICI monotherapy as reference. CONCLUSIONS: Compared with ICI monotherapy, ICI combined with RT, rather than with CHEMO or TARGET, is associated with a higher risk of IP in NSCLC patients. Hence, patients receiving these treatments should be carefully monitored for IP.

PARP Inhibition Induces Synthetic Lethality and Adaptive Immunity in LKB1-Mutant Lung Cancer.

Contradictory characteristics of elevated mutational burden and a "cold" tumor microenvironment (TME) coexist in liver kinase B1 (LKB1)-mutant non-small cell lung cancers (NSCLC). The molecular basis underlying this paradox and strategies tailored to these historically difficult to treat cancers are lacking. Here, by mapping the single-cell transcriptomic landscape of genetically engineered mouse models with Kras versus Kras/Lkb1-driven lung tumors, we detected impaired tumor-intrinsic IFNγ signaling in Kras/Lkb1-driven tumors that explains the inert immune context. Mechanistic analysis showed that mutant LKB1 led to deficiency in the DNA damage repair process and abnormally activated PARP1. Hyperactivated PARP1 attenuated the IFNγ pathway by physically interacting with and enhancing the poly(ADP-ribosyl)ation of STAT1, compromising its phosphorylation and activation. Abrogation of the PARP1-driven program triggered synthetic lethality in NSCLC on the basis of the LKB1 mutation-mediated DNA repair defect, while also restoring phosphorylated STAT1 to favor an immunologically "hot" TME. Accordingly, PARP1 inhibition restored the disrupted IFNγ signaling and thus mounted an adaptive immune response to synergize with PD-1 blockade in multiple LKB1-deficient murine tumor models. Overall, this study reveals an unexplored interplay between the DNA repair process and adaptive immune response, providing a molecular basis for dual PARP1 and PD-1 inhibition in treating LKB1-mutant NSCLC. SIGNIFICANCE: Targeting PARP exerts dual effects to overcome LKB1 loss-driven immunotherapy resistance through triggering DNA damage and adaptive immunity, providing a rationale for dual PARP and PD-1 inhibition in treating LKB1-mutant lung cancers.

Use of computed tomography-derived body composition to determine the prognosis of patients with primary liver cancer treated with immune checkpoint inhibitors: a retrospective cohort study.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have been used to successfully treat primary liver cancer (PLC); however, identifying modifiable patient factors associated with therapeutic benefits is challenging. Obesity is known to be associated with increased survival after ICI treatment; however, the relationship between body composition (muscle, fat) and outcomes is unclear. This study aimed to evaluate the association between sarcopenia and CT-derived fat content and the prognosis of ICIs for the treatment of PLC. METHODS: In this retrospective cohort study of 172 patients with PLC, we measured the skeletal muscle index (SMI), skeletal muscle density, visceral adipose tissue index, subcutaneous adipose tissue index, total adipose tissue index (TATI), and visceral-to-subcutaneous adipose tissue area ratio using CT. In addition, we analyzed the impact of body composition on the prognosis of the patients. Multivariate Cox regression analysis was used to screen for influencing factors. RESULTS: Among the seven body composition components, low SMI (sarcopenia) and low TATI were significantly associated with poor clinical outcomes. Multivariate analysis revealed that sarcopenia (hazard ratio [HR], 5.39; 95% confidence interval [CI], 1.74-16.74; p = 0.004) was a significant predictor of overall survival (OS). Kaplan-Meier curves showed that sarcopenia and TATI were significant predictors of OS. Body mass index was not associated with survival outcomes. CONCLUSIONS: Sarcopenia and fat tissue content appear to be independently associated with reduced survival rates in patients with PLC treated with ICIs.

Splenomegaly in predicting the survival of patients with advanced primary liver cancer treated with immune checkpoint inhibitors.

BACKGROUND & AIMS: Immune checkpoint inhibitors (ICIs) play an increasingly important role in the treatment of primary liver cancer (PLC). Some patients with PLC experience symptoms of splenomegaly. Splenomegaly may affect the efficacy of ICIs due to an imbalance of the immune microenvironment. Currently, there is a lack of evidence on the relationship between splenomegaly and prognosis in patients with PLC treated with ICIs. This study analyzed the relationship between splenomegaly and prognosis in patients with PLC treated with ICIs. METHODS: In this retrospective cohort study of 161 patients with PLC treated with ICIs, splenomegaly was diagnosed using computed tomography or magnetic resonance imaging and the impact of splenomegaly on patient survival was analyzed. RESULTS: Through univariate and multivariate Cox regression analyses, we determined that splenomegaly was associated with shortened overall survival (p = 0.002) and progression-free survival (p = 0.013) in patients with PLC treated with ICIs. Kaplan-Meier analysis further validated our results. The overall survival and progression-free survival of patients with splenomegaly were significantly shorter than those of patients without splenomegaly (p < 0.01 and p = 0.02, respectively). CONCLUSIONS: We concluded that splenomegaly was a predictor of prognosis in patients with PLC treated with ICIs. This is the first study to report this important finding.

Organ-specific metastatic landscape dissects PD-(L)1 blockade efficacy in advanced non-small cell lung cancer: applicability from clinical trials to real-world practice.

BACKGROUND: Organ-specific metastatic context has not been incorporated into the clinical practice of guiding programmed death-(ligand) 1 [PD-(L)1] blockade, due to a lack of understanding of its predictive versus prognostic value. We aim at delineating and then incorporating both the predictive and prognostic effects of the metastatic-organ landscape to dissect PD-(L)1 blockade efficacy in non-small cell lung cancer (NSCLC). METHODS: A total of 2062 NSCLC patients from a double-arm randomized trial (OAK), two immunotherapy trials (FIR, BIRCH), and a real-world cohort (NFyy) were included. The metastatic organs were stratified into two categories based on their treatment-dependent predictive significance versus treatment-independent prognosis. A metastasis-based scoring system (METscore) was developed and validated for guiding PD-(L)1 blockade in clinical trials and real-world practice. RESULTS: Patients harboring various organ-specific metastases presented significantly different responses to immunotherapy, and those with brain and adrenal gland metastases survived longer than others [overall survival (OS), p = 0.0105; progression-free survival (PFS), p = 0.0167]. In contrast, survival outcomes were similar in chemotherapy-treated patients regardless of metastatic sites (OS, p = 0.3742; PFS, p = 0.8242). Intriguingly, the immunotherapeutic predictive significance of the metastatic-organ landscape was specifically presented in PD-L1-positive populations (PD-L1 > 1%). Among them, a paradoxical coexistence of a favorable predictive effect coupled with an unfavorable prognostic effect was observed in metastases to adrenal glands, brain, and liver (category I organs), whereas metastases to bone, pleura, pleural effusion, and mediastinum yielded consistent unfavorable predictive and prognostic effects (category II organs). METscore was capable of integrating both predictive and prognostic effects of the entire landscape and dissected OS outcome of NSCLC patients received PD-(L)1 blockade (p < 0.0001) but not chemotherapy (p = 0.0805) in the OAK training cohort. Meanwhile, general performance of METscore was first validated in FIR (p = 0.0350) and BIRCH (p < 0.0001), and then in the real-world NFyy cohort (p = 0.0181). Notably, METscore was also applicable to patients received PD-(L)1 blockade as first-line treatment both in the clinical trials (OS, p = 0.0087; PFS, p = 0.0290) and in the real-world practice (OS, p = 0.0182; PFS, p = 0.0045). CONCLUSIONS: Organ-specific metastatic landscape served as a potential predictor of immunotherapy, and METscore might enable noninvasive forecast of PD-(L)1 blockade efficacy using baseline radiologic assessments in advanced NSCLC.

Assessment of anti-PD-(L)1 for patients with coexisting malignant tumor and tuberculosis classified by active, latent, and obsolete stage.

BACKGROUND: It is not a rare clinical scenario to have patients presenting with coexisting malignant tumor and tuberculosis. Whether it is feasible to conduct programmed death-(ligand) 1 [PD-(L)1] inhibitors to these patients, especially those with active tuberculosis treated with concurrent anti-tuberculosis, is still unknown. METHODS: This study enrolled patients with coexisting malignancy and tuberculosis and treated with anti-PD-(L)1 from Jan 2018 to July 2021 in 2 institutions. The progression-free survival (PFS), objective response rate (ORR), and safety of anti-PD-(L)1 therapy, as well as response to anti-tuberculosis treatment, were evaluated. RESULTS: A total of 98 patients were screened from this cohort study, with 45 (45.9%), 21 (21.4%), and 32 (32.7%) patients diagnosed with active, latent, and obsolete tuberculosis, respectively. The overall ORR was 36.0% for anti-PD-(L)1 therapy, with 34.2%, 35.5%, and 41.2% for each subgroup. Median PFS was 8.0 vs 6.0 vs 6.0 months (P=0.685) for each subgroup at the time of this analysis. For patients with active tuberculosis treated with concurrent anti-tuberculosis, median duration of anti-tuberculosis therapy was 10.0 (95% CI, 8.01-11.99) months. There were 83.3% (20/24) and 93.3% (42/45) patients showing sputum conversion and radiographic response, respectively, after anti-tuberculosis therapy, and two patients experienced tuberculosis relapse. Notably, none of the patients in latent and only one patient in obsolete subgroups showed tuberculosis induction or relapse after anti-PD-(L)1 therapy. Treatment-related adverse events (TRAEs) occurred in 33 patients (73.3%) when treated with concurrent anti-PD-(L)1 and anti-tuberculosis. Grade 3 or higher TRAEs were hematotoxicity (n = 5, 11.1%), and one patient suffered grade 3 pneumonitis leading to the discontinuation of immunotherapy. CONCLUSIONS: This study demonstrated that patients with coexisting malignant tumor and tuberculosis benefited equally from anti-PD-(L)1 therapy, and anti-tuberculosis response was unimpaired for those with active tuberculosis. Notably, the combination of anti-PD-(L)1 and anti-tuberculosis therapy was well-tolerated without significant unexpected toxic effects.

Lung metastasis and lymph node metastasis are risk factors for hyperprogressive disease in primary liver cancer patients treated with immune checkpoint inhibitors.

BACKGROUND: At present, some cancer patients experience hyperprogressive disease (HPD) after receiving immunotherapy. This study used the Response Evaluation Criteria in Solid Tumors 1.1 to evaluate the incidence of HPD in patients receiving immune checkpoint inhibitors (ICIs) for treating primary liver cancer (PLC) and to explore the risk factors for HPD. METHODS: This retrospective, single-center study included patients with PLC who were treated with ICIs. The RECIST 1.1 was used to determine patients with HPD. Univariate and multivariate regression analyses were performed to explore the risk factors for HPD, and clinical variables with prognostic significance for HPD were included to establish a risk model. RESULTS: Among 129 patients with PLC treated with ICIs, HPD occurred in 13 patients (10.1%). In the multivariate regression analysis, lymph node metastasis and lung metastasis were risk factors for HPD. The area under the curve of the risk model, established by including lymph node metastasis, lung metastasis, neutrophil-lymphocyte ratio, albumin, and performance status, was 0.801 (P<0.001). The progression-free survival of HPD patients was significantly worse than that of non-HPD patients (P<0.001). CONCLUSIONS: In this study, 10.1% of patients with PLC had HPD. Compared with the non-HPD patients, lung metastasis and lymph node metastasis were independent risk factors of HPD.

De Novo Mutation in Non-Tyrosine Kinase Domain of ROS1 as a Potential Predictor of Immune Checkpoint Inhibitors in Melanoma.

PURPOSE: Despite the success of targeted therapy in c-ros oncogene 1 (ROS1)-rearranged cancers, especially non-small cell lung cancer (NSCLC), the clinical significance of ROS1 de novo mutation has not yet been understood. We sought to elucidate the predictive effect of ROS1 mutation for immune checkpoint inhibitor (ICI) therapy in melanoma. METHODS: The Cancer Genome Atlas [TCGA (n = 10967)] and Memorial Sloan Kettering Cancer Center [MSK (n = 10,945)] datasets, as well as two clinical cohorts of melanoma received ICI [CA209-038 (n = 73) and MEL-IPI (n = 110)], were included to explore the prevalence, prognostic effect, and immunotherapeutic predictive effect of ROS1 mutation in melanoma. Overall survival (OS) was defined as the primary outcome. RESULTS: Overall, melanoma accounted for the highest proportion of ROS1 mutation (~20%) which made up the majority (~95%) of the ROS1-alterated cases. Remarkably, ROS1 mutation yielded longer OS from ICI than the wild-type counterpart in the MSK melanoma population [hazard ratio (HR) 0.47, 95% confidence interval (CI) 0.30-0.74], and two external melanoma cohorts (CA209-038: HR 0.42, 95% CI 0.20-0.89; MEL-IPI: HR 0.55, 95% CI 0.34-0.91), without affecting the prognosis of patients. Elevated tumor mutational burden and enrichment of DNA damage repair was observed in ROS1 mutated patients, providing an explanation for the favorable responses to ICI therapy. Precisely, ROS1 mutation in non-protein tyrosine kinase (PTK) domain but not PTK mutation was responsible for the immunotherapy-specific responses of the ROS1 mutated patients in melanoma. CONCLUSIONS: Collectively, ROS1 mutation, specifically the non-PTK mutation, is a potential predictor of ICI therapy in melanoma, which is distinct from the well-established role of ROS1 rearrangement for targeted therapy in NSCLC.

Efficacy and Treatment Strategies in Advanced Cancers with Liver Metastasis Receiving Atezolizumab Therapy.

BACKGROUND: Atezolizumab has been used to treat patients with liver metastasis (LM). However, whether atezolizumab is superior to standard of care therapy in an all-comer or selective population with LM is still uncertain. METHODS: A pooled analysis based on 10 randomized controlled trials was conducted to evaluate the clinical benefit of atezolizumab versus standard therapy in patients stratified by liver metastatic status, followed by biomarker-based individual analyses of the non-small cell lung cancer (NSCLC) cohort (OAK and POPLAR studies) and urothelial cancer cohort (IMvigor210 study). RESULTS: The pooled analysis demonstrated an overall survival (OS) improvement using atezolizumab treatment versus standard therapy across cancer types and treatment lines regardless of liver metastatic status. However, the efficacy of atezolizumab in patients with LM from the second-line setting was limited, based on the individual analysis of NSCLC cohorts (P = 0.053). PD-L1 strong expression emerged as a predominant biomarker (P = 0.015) to screen atezolizumab-advantageous patients with LM. Notably, the combination of PD-L1 and LM improved the predictive power for atezolizumab therapy in both NSCLC and urothelial cancer cohorts. Exploratory translational analysis revealed that strong expression of PD-L1 might have reversed the non-inflamed immune phenotype of liver metastasis, thus sensitizing these patients to immunotherapy. CONCLUSION: Our study demonstrated a preferable efficacy of atezolizumab in patients with LM as first-line therapy over standard of care therapy, while sensitive patients should be selected in second-line settings. PD-L1 was demonstrated as the most effective biomarker for screening atezolizumab-advantageous patients with LM.

Integrative evaluation of primary and metastatic lesion spectrum to guide anti-PD-L1 therapy of non-small cell lung cancer: results from two randomized studies.

Objectives: Clinical benefits of immune-checkpoint blockade (ICB) versus standard chemotherapy have been established in unselected non-small cell lung cancer (NSCLC). However, the response to ICB therapy among patients is heterogeneous in clinical practice. Materials and Methods: We retrospectively assessed the predicitive effect of the primary and metastatic lesion spectrum (baseline sum of the longest diameters [SLD], number of metastatic sites and specific organ metastases) on the efficacy of atezolizumab over docetaxel in OAK and POPLAR trial cohorts. A decision model, termed DSO (Diameter-Site-Organ), based on the spectrum was developed and validated for guiding ICB. Results: Higher SLD (>38 mm) and more metastatic sites (≥2) were characterized with pronounced overall survival (OS) benefits from atezolizumab versus docetaxel. Specifically, adrenal gland and brain metastases were identified as favorable predictors of atezolizumab treatment. The DSO model was developed in the discovery cohort to integrate the directive effect of the primary and metastatic lesion spectrum. Remarkably, a general pattern of enhanced efficacy of atezolizumab versus docetaxel was observed along with the increase of the DSO score. For patients with DSO score > 0, atezolizumab yielded a significantly prolonged OS than docetaxel, whereas OS was generally similar between two treatments in patients with DSO score ≤ 0. Equivalent findings were also seen in the internal and external validation cohorts. Conclusions: The response to anti-PD-L1 therapy among patients varied with the primary and metastatic lesion spectrum. The DSO-based system might provide promising medication guidance for ICB treatment in NSCLC patients.

Inferring Homologous Recombination Deficiency of Ovarian Cancer From the Landscape of Copy Number Variation at Subchromosomal and Genetic Resolutions.

BACKGROUND: Homologous recombination deficiency (HRD) is characterized by overall genomic instability and has emerged as an indispensable therapeutic target across various tumor types, particularly in ovarian cancer (OV). Unfortunately, current detection assays are far from perfect for identifying every HRD patient. The purpose of this study was to infer HRD from the landscape of copy number variation (CNV). METHODS: Genome-wide CNV landscape was measured in OV patients from the Australian Ovarian Cancer Study (AOCS) clinical cohort and >10,000 patients across 33 tumor types from The Cancer Genome Atlas (TCGA). HRD-predictive CNVs at subchromosomal resolution were identified through exploratory analysis depicting the CNV landscape of HRD versus non-HRD OV patients and independently validated using TCGA and AOCS cohorts. Gene-level CNVs were further analyzed to explore their potential predictive significance for HRD across tumor types at genetic resolution. RESULTS: At subchromosomal resolution, 8q24.2 amplification and 5q13.2 deletion were predominantly witnessed in HRD patients (both p < 0.0001), whereas 19q12 amplification occurred mainly in non-HRD patients (p < 0.0001), compared with their corresponding counterparts within TCGA-OV. The predictive significance of 8q24.2 amplification (p < 0.0001), 5q13.2 deletion (p = 0.0056), and 19q12 amplification (p = 0.0034) was externally validated within AOCS. Remarkably, pan-cancer analysis confirmed a cross-tumor predictive role of 8q24.2 amplification for HRD (p < 0.0001). Further analysis of CNV in 8q24.2 at genetic resolution revealed that amplifications of the oncogenes, MYC (p = 0.0001) and NDRG1 (p = 0.0004), located on this fragment were also associated with HRD in a pan-cancer manner. CONCLUSIONS: The CNV landscape serves as a generalized predictor of HRD in cancer patients not limited to OV. The detection of CNV at subchromosomal or genetic resolution could aid in the personalized treatment of HRD patients.

Development and interpretation of a pathomics-based model for the prediction of microsatellite instability in Colorectal Cancer.

Microsatellite instability (MSI) has been approved as a pan-cancer biomarker for immune checkpoint blockade (ICB) therapy. However, current MSI identification methods are not available for all patients. We proposed an ensemble multiple instance deep learning model to predict microsatellite status based on histopathology images, and interpreted the pathomics-based model with multi-omics correlation. Methods: Two cohorts of patients were collected, including 429 from The Cancer Genome Atlas (TCGA-COAD) and 785 from an Asian colorectal cancer (CRC) cohort (Asian-CRC). We established the pathomics model, named Ensembled Patch Likelihood Aggregation (EPLA), based on two consecutive stages: patch-level prediction and WSI-level prediction. The initial model was developed and validated in TCGA-COAD, and then generalized in Asian-CRC through transfer learning. The pathological signatures extracted from the model were analyzed with genomic and transcriptomic profiles for model interpretation. Results: The EPLA model achieved an area-under-the-curve (AUC) of 0.8848 (95% CI: 0.8185-0.9512) in the TCGA-COAD test set and an AUC of 0.8504 (95% CI: 0.7591-0.9323) in the external validation set Asian-CRC after transfer learning. Notably, EPLA captured the relationship between pathological phenotype of poor differentiation and MSI (P < 0.001). Furthermore, the five pathological imaging signatures identified from the EPLA model were associated with mutation burden and DNA damage repair related genotype in the genomic profiles, and antitumor immunity activated pathway in the transcriptomic profiles. Conclusions: Our pathomics-based deep learning model can effectively predict MSI from histopathology images and is transferable to a new patient cohort. The interpretability of our model by association with pathological, genomic and transcriptomic phenotypes lays the foundation for prospective clinical trials of the application of this artificial intelligence (AI) platform in ICB therapy.

Development and Validation of a Prognostic Nomogram Based on Residual Tumor in Patients With Nondisseminated Nasopharyngeal Carcinoma.

OBJECTIVES: To investigate the prognostic value of residual tumor based on Magnetic resonance imaging(MRI) and establish an effective prognostic nomogram model referring to clinical,pathological and other related factors for predicting prognosis in nasopharyngeal carcinoma. METHODS: Overall, 538 patients with non-metastatic, histologically-confirmed nasopharyngeal carcinoma were retrospectively examined. Data from 397 patients were used for the construction and validation of a nomogram based on the presence of residual tumor. A concordance index (C-index) was employed to assess the predictive accuracy and discriminative ability of the nomogram. RESULTS: The 3-year survival rates in the non-residual and residual tumor cohorts were as follows: progression-free survival, 73.4% vs. 61.0%, P = 0.009; locoregional recurrence-free survival, 81.9% vs. 72.0%, P = 0.02; and distant metastasis-free survival, 80.7% vs. 73.5%, P = 0.11. Nine significant factors were included in the nomogram model. The calibration curve for the probability of progression-free survival showed that the nomogram-based predictive values had good concordance with the actual observations. CONCLUSION: The results showed that the patients in the residual tumor cohorts had a worse prognosis.The proposed nomogram may predict the prognosis and guide clinical decision-making concerning local residual tumors in nasopharyngeal carcinoma patients. Patients with a high risk of progression require more timely and aggressive treatment.

Development and validation of a genomic mutation signature to predict response to PD-1 inhibitors in non-squamous NSCLC: a multicohort study

BACKGROUND: Genetic variations of some driver genes in non-small cell lung cancer (NSCLC) had shown potential impact on immune microenvironment and associated with response or resistance to programmed cell death protein 1 (PD-1) blockade immunotherapy. We therefore undertook an exploratory analysis to develop a genomic mutation signature (GMS) and predict the response to anti-PD-(L)1 therapy. METHODS: In this multicohort analysis, 316 patients with non-squamous NSCLC treated with anti-PD-(L)1 from three independent cohorts were included in our study. Tumor samples from the patients were molecularly profiled by MSK-IMPACT or whole exome sequencing. We developed a risk model named GMS based on the MSK training cohort (n=123). The predictive model was first validated in the separate internal MSK cohort (n=82) and then validated in an external cohort containing 111 patients from previously published clinical trials. RESULTS: A GMS risk model consisting of eight genes (TP53, KRAS, STK11, EGFR, PTPRD, KMT2C, SMAD4, and HGF) was generated to classify patients into high and low GMS groups in the training cohort. Patients with high GMS in the training cohort had longer progression-free survival (hazard ratio (HR) 0.41, 0.28-0.61, p<0.0001) and overall survival (HR 0.53, 0.32-0.89, p=0.0275) compared with low GMS. We noted equivalent findings in the internal validation cohort and in the external validation cohort. The GMS was demonstrated as an independent predictive factor for anti-PD-(L)1 therapy comparing with tumor mutational burden. Meanwhile, GMS showed undifferentiated predictive value in patients with different clinicopathological features. Notably, both GMS and PD-L1 were independent predictors and demonstrated poorly correlated; inclusion of PD-L1 with GMS further improved the predictive capacity for PD-1 blockade immunotherapy. CONCLUSIONS: Our study highlights the potential predictive value of GMS for immunotherapeutic benefit in non-squamous NSCLC. Besides, the combination of GMS and PD-L1 may serve as an optimal partner in guiding treatment decisions for anti-PD-(L)1 based therapy.

Radiomics-based nomogram using CT imaging for noninvasive preoperative prediction of early recurrence in patients with hepatocellular carcinoma.

PURPOSE: The aim of this study was to develop and validate a radiomics nomogram based on radiomics features and clinical data for the non-invasive preoperative prediction of early recurrence (≤2 years) in patients with hepatocellular carcinoma (HCC). METHODS: We enrolled 262 HCC patients who underwent preoperative contrast-enhanced computed tomography and curative resection (training cohort, n=214; validation cohort, n=48). We applied propensity score matching (PSM) to eliminate redundancy between clinical characteristics and image features, and the least absolute shrinkage and selection operator (LASSO) was used to prevent overfitting. Next, a radiomics signature, clinical nomogram, and combined clinical-radiomics nomogram were built to predict early recurrence, and we compared the performance and generalization of these models. RESULTS: The radiomics signature stratified patients into low-risk and high-risk, which show significantly difference in recurrence free survival and overall survival (P ≤ 0.01). Multivariable analysis identified dichotomised radiomics signature, alpha fetoprotein, and tumour number and size as key early recurrence indicators, which were incorporated into clinical and radiomics nomograms. The radiomics nomogram showed the highest area under the receiver operating characteristic curve (AUC), with significantly superior predictive performance over the clinical nomogram in the training cohort (0.800 vs 0.716, respectively; P = 0.001) and the validation cohort (0.785 vs 0.654, respectively; P = 0.039). CONCLUSION: The radiomics nomogram is a non-invasive preoperative biomarker for predicting early recurrence in patients with HCC. This model may be of clinical utility for guiding surveillance follow-ups and identifying optimal interventional strategies.

HPV-positive status associated with inflamed immune microenvironment and improved response to anti-PD-1 therapy in head and neck squamous cell carcinoma.

Chemotherapy and radiotherapy predominantly improve the clinical outcomes of patients with human papillomavirus (HPV)-related head and neck squamous cell carcinoma (HNSCC). Whether this superiority goes on when treated with immune checkpoint inhibitors is still unclear. This study sought to determine the predictive value and potential mechanisms of HPV status for the treatment of programmed cell death 1 (PD-1)/ligand 1(PD-L1) inhibitors. We conducted an integrated analysis of the relationships between HPV status and PD-L1, tumor mutation burden (TMB) and inflammation-related immune cells and molecules, based on the analysis of repository databases and resected HNSCC specimens. The pooled analysis of overall survival (OS) and objective response rate (ORR) suggested that HPV-positive patients benefited more from PD-1/PD-L1 inhibitors than HPV-negative patients (OS: hazard ratio (HR) = 0.71, p = 0.02; ORR: 21.9% vs 14.1%, odds ratio (OR) = 1.79, p = 0.01). Analysis of public databases and resected HNSCC specimens revealed that HPV status was independent of PD-L1 expression and TMB in HNSCC. However, HPV infection significantly increased T-cell infiltration, immune effector cell activation and the diversity of T-cell receptors. Notably, HPV-positivity correlated with increased immune cytolytic activity and a T-cell-inflamed gene expression profile. This work provides evidence that HPV status can be used to predict the effectiveness of PD-1 inhibitors in HNSCC, independently of PD-L1 expression and TMB, and probably results from an inflamed immune microenvironment induced by HPV infection.