An exploratory study of whether axillary lymph node dissection can be avoided in breast cancer patients with positive lymph nodes.

Background: Breast cancer patients with positive axillary lymph nodes usually require axillary lymph node dissection (ALND), with many postoperative complications, such as lymphedema. For these patients, whether sentinel lymph node biopsy (SLNB) can replace ALND has been a research hotspot in the field of breast cancer. This study developed two risk stratification models for predicting the clinical outcomes of breast cancer patients with positive axillary lymph nodes receiving SLNB alone or ALND to determine which patients could potentially avoid ALND. Methods: A total of 21,942 breast cancer patients, including a training set (n=15,362) and a testing set (n=6,580), were enrolled in this study from Surveillance, Epidemiology, and End Results (SEER) between 2000 and 2017. The risk factors associated with breast cancer-specific survival (BCSS) and overall survival (OS) were evaluated using multivariate Cox regression analysis and then integrated into nomograms and risk stratification models examined by receiver operating characteristic (ROC) curves and calibration curves. The survival discrepancies were compared between the SLNB and ALND subgroups with different risk scores with Kaplan-Meier plots. Results: In multivariate Cox regression analyses, grade, marital status, T stage, radiotherapy and lymph node metastasis (GMTRL) were independent risk factors in breast cancer patients with both OS and BCSS status in the ALND cohort from the training set. Nomograms have been developed based on these factors to predict 3- and 5-year OS and BCSS in patients with ALND. Calibration curves and ROC curves in both the training and testing sets confirmed the excellent overall predictive performance of the nomograms. Furthermore, we developed two risk stratification models based on OS and BCSS status, revealing that patients with low GMTRL scores might avoid ALND in both OS and BCSS status [OS: hazard ratio (HR) =0.929, 95% confidence interval (CI): 0.841-1.027, P=0.150; BCSS: HR =0.953, 95% CI: 0.831-1.094, P=0.495], but patients with moderate (OS: HR =0.756, 95% CI: 0.666-0.859, P<0.001; BCSS: HR =0.643, 95% CI: 0.537-0.768, P<0.001) and high GMTRL scores could not (OS: HR =0.719, 95% CI: 0.549-0.940, P=0.014; BCSS: HR =0.731, 95% CI: 0.549-0.974, P=0.031). Conclusions: Breast cancer patients with positive nodes could be treated with SLNB alone rather than ALND without affecting prognosis based on GMTRL scores. Patients with high or moderate GMTRL scores benefited greatly from ALND, but not for patients with low GMTRL scores. This study may assist clinicians in tailoring treatments.

Machine-learning-based classification of diffuse large B-cell lymphoma patients by a 7-mRNA signature enriched with immune infiltration and cell cycle.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) exhibits remarkable heterogeneity but still remains undiagnosed in identifying the subpopulation of DLBCL to predict the prognosis and guide clinical treatment. METHODS: Molecular subgroups were identified in gene expression data from GSE10846 by a consensus clustering algorithm. And gene set enrichment analysis, immune infiltration, and the proposed cell cycle algorithm were applied to explore the biological functions of different subtypes. Meanwhile, univariate and multivariate Cox regression analyses were used to evaluate independent prognostic factors of DLBCL. Finally, the prognostic model, including some key genes screened by Lasso regression, Random Forest algorithm, and point-biserial correlation, was constructed by an optimal classifier from seven machine learning algorithms and validated by another three external datasets (GSE34171, GSE87371, GSE31312). RESULTS: Comprehensive genomic analysis of 1,143 DLBCL samples identify 2 molecularly, prognostically relevant subtypes: immune-enriched (IME) and cell-cycle-enriched (CCE). Then a new predictive model including seven key genes (SERPING1, TIMP2, NME1, DCTPP1, RFC4, POLE2, and SNRPD1) was developed with high prediction accuracy (88.6%) and strong predictive power (AUC = 0.973) based on the Support Vector Machine (SVM) algorithm in 414 patients from GSE10846. The predictive power was similar in another three testing sets (HR > 1.400, p < 0.05). CONCLUSION: This model could evaluate survival independently with strong predictive power compared with other clinical risk factors. Our study constructed a reliable model to predict two new subtypes of DLBCL patients, which could guide the implementation of individualized treatment.

Applications of photodynamic therapy in extramammary Paget's disease.

Extramammary Paget's disease (EMPD) is a rare form of adenocarcinoma usually found in apocrine gland-containing cutaneous regions. EMPD affects the vulvar area most commonly, followed by the perianal area, scrotum, penis, and axillary region. In its initial form, EMPD presents as an erythematous plaque with well-defined edges, fine scaling, excoriations, exulcerations, and lichenification. Generally, a definitive diagnosis can be made through histopathological analysis. Importantly, associated malignancies should be investigated prior to treatment initiation. Photodynamic therapy (PDT) is a modern, noninvasive treatment strategy for non-oncological diseases as well as various cancers. In recent years, PDT has been widely used to treat EMPD. This present article presents a discussion of the diagnosis and treatment of EMPD as well as the usefulness of PDT in its management.

Integrative analysis identifies two molecular and clinical subsets in Luminal B breast cancer.

Comprehensive multiplatform analysis of Luminal B breast cancer (LBBC) specimens identifies two molecularly distinct, clinically relevant subtypes: Cluster A associated with cell cycle and metabolic signaling and Cluster B with predominant epithelial mesenchymal transition (EMT) and immune response pathways. Whole-exome sequencing identified significantly mutated genes including TP53, PIK3CA, ERBB2, and GATA3 with recurrent somatic mutations. Alterations in DNA methylation or transcriptomic regulation in genes (FN1, ESR1, CCND1, and YAP1) result in tumor microenvironment reprogramming. Integrated analysis revealed enriched biological pathways and unexplored druggable targets (cancer-testis antigens, metabolic enzymes, kinases, and transcription regulators). A systematic comparison between mRNA and protein displayed emerging expression patterns of key therapeutic targets (CD274, YAP1, AKT1, and CDH1). A potential ceRNA network was developed with a significantly different prognosis between the two subtypes. This integrated analysis reveals a complex molecular landscape of LBBC and provides the utility of targets and signaling pathways for precision medicine.

An exploration of the correlations between seven psychiatric disorders and the risks of breast cancer, breast benign tumors and breast inflammatory diseases: Mendelian randomization analyses.

Background: Previous observational studies have showed that certain psychiatric disorders may be linked to breast cancer risk, there is, however, little understanding of relationships between mental disorders and a variety of breast diseases. This study aims to investigate if mental disorders influence the risks of overall breast cancer, the two subtypes of breast cancer (ER+ and ER-), breast benign tumors and breast inflammatory diseases. Methods: During our research, genome-wide association study (GWAS) data for seven psychiatric disorders (schizophrenia, major depressive disorder, bipolar disorder, post-traumatic stress disorder, panic disorder, obsessive-compulsive disorder and anorexia nervosa) from the Psychiatric Genomics Consortium (PGC) and the UK Biobank were selected, and single-nucleotide polymorphisms (SNPs) significantly linked to these mental disorders were identified as instrumental variables. GWAS data for breast diseases came from the Breast Cancer Association Consortium (BCAC) as well as the FinnGen consortium. We performed two-sample Mendelian randomization (MR) analyses and multivariable MR analyses to assess these SNPs' effects on various breast diseases. Both heterogeneity and pleiotropy were evaluated by sensitivity analyses. Results: When the GWAS data of psychiatric disorders were derived from the PGC, our research found that schizophrenia significantly increased the risks of overall breast cancer (two-sample MR: OR 1.05, 95%CI [1.03-1.07], p = 3.84 × 10-6; multivariable MR: OR 1.06, 95%CI [1.04-1.09], p = 2.34 × 10-6), ER+ (OR 1.05, 95%CI [1.02-1.07], p = 5.94 × 10-5) and ER- (two-sample MR: OR 1.04, 95%CI [1.01-1.07], p = 0.006; multivariable MR: OR 1.06, 95%CI [1.02-1.10], p = 0.001) breast cancer. Nevertheless, major depressive disorder only showed significant positive association with overall breast cancer (OR 1.12, 95%CI [1.04-1.20], p = 0.003) according to the two-sample MR analysis, but not in the multivariable MR analysis. In regards to the remainder of the mental illnesses and breast diseases, there were no significant correlations. While as for the data from the UK Biobank, schizophrenia did not significantly increase the risk of breast cancer. Conclusions: The correlation between schizophrenia and breast cancer found in this study may be false positive results caused by underlying horizontal pleiotropy, rather than a true cause-and-effect relationship. More prospective studies are still needed to be carried out to determine the definitive links between mental illnesses and breast diseases.

Evaluation of Male Breast Cancer and the Application of Sentinel Lymph Node Biopsy: A Multicenter Retrospective Study.

Sentinel lymph node biopsy (SLNB) is currently used as a routine treatment for patients with breast cancer. However, it may not be applicable for patients with male breast cancer (MBC), because they have notably different clinicopathological features from those occurring in females. There is a lack of evidence of SLNB application and safe exemption from axillary lymph node dissection (ALND) in patients with MBC. This study aimed to evaluate the application of SLNB to provide information for the standardized treatment of patients with MBC. The MBC patient records from 4 institutions ranging from January 2001 to November 2020 were retrospectively reviewed. There were 220 patients with MBC with a median age of 60 (range 24-88) years and an average tumor size of 2.3 cm (range 0.5 cm-6.5 cm). Sixty-six percent of patients underwent SLNB, and 39% of them showed positive results. A total of 157 patients underwent ALND, while only half of them had positive nodes, causing unnecessary complications. For patients in the clinical early stage, we found that the SLNB showed a noninferiority to the ALND treatment in DFS (P = .18) and OS (P = .055). In conclusion, there are certain obstacles to the broad application of SLNB due to the lower proportion of patients with clinically negative lymph nodes. However, it is undeniable that SLNB can safely and effectively exempt patients with MBC at early stage with clinically negative nodes from ALND to reduce subsequent complications. It is still an ideal criterion for the axillary staging of patients with MBC.

Proteogenomic landscape of gastric adenocarcinoma peritoneal metastases.

Advanced gastric adenocarcinoma (GAC) often leads to peritoneal carcinomatosis (PC) and is associated with very poor outcome. Here we report the comprehensive proteogenomic study of ascites derived cells from a prospective GAC cohort (n = 26 patients with peritoneal carcinomatosis, PC). A total of 16,449 proteins were detected from whole cell extracts (TCEs). Unsupervised hierarchical clustering resulted in three distinct groups that reflected extent of enrichment in tumor cells. Integrated analysis revealed enriched biological pathways and notably, some druggable targets (cancer-testis antigens, kinases, and receptors) that could be exploited to develop effective therapies and/or tumor stratifications. Systematic comparison of expression levels of proteins and mRNAs revealed special expression patterns of key therapeutics target notably high mRNA and low protein expression of HAVCR2 (TIM-3), and low mRNA but high protein expression of cancer-testis antigens CTAGE1 and CTNNA2. These results inform strategies to target GAC vulnerabilities.

Infiltrating myeloid cell diversity determines oncological characteristics and clinical outcomes in breast cancer.

BACKGROUND: Breast cancer presents as one of the top health threats to women around the world. Myeloid cells are the most abundant cells and the major immune coordinator in breast cancer tumor microenvironment (TME), target therapies that harness the anti-tumor potential of myeloid cells are currently being evaluated in clinical trials. However, the landscape and dynamic transition of myeloid cells in breast cancer TME are still largely unknown. METHODS: Myeloid cells were characterized in the single-cell data and extracted with a deconvolution algorithm to be assessed in bulk-sequencing data. We used the Shannon index to describe the diversity of infiltrating myeloid cells. A 5-gene surrogate scoring system was then constructed and evaluated to infer the myeloid cell diversity in a clinically feasible manner. RESULTS: We dissected the breast cancer infiltrating myeloid cells into 15 subgroups including macrophages, dendritic cells (DCs), and monocytes. Mac_CCL4 had the highest angiogenic activity, Mac_APOE and Mac_CXCL10 were highly active in cytokine secretion, and the DCs had upregulated antigen presentation pathways. The infiltrating myeloid diversity was calculated in the deconvoluted bulk-sequencing data, and we found that higher myeloid diversity was robustly associated with more favorable clinical outcomes, higher neoadjuvant therapy responses, and a higher rate of somatic mutations. We then used machine learning methods to perform feature selection and reduction, which generated a clinical-friendly scoring system consisting of 5 genes (C3, CD27, GFPT2, GMFG, and HLA-DPB1) that could be used to predict clinical outcomes in breast cancer patients. CONCLUSIONS: Our study explored the heterogeneity and plasticity of breast cancer infiltrating myeloid cells. By using a novel combination of bioinformatic approaches, we proposed the myeloid diversity index as a new prognostic metric and constructed a clinically practical scoring system to guide future patient evaluation and risk stratification.

Establishment and validation of a multigene model to predict the risk of relapse in hormone receptor-positive early-stage Chinese breast cancer patients.

BACKGROUND: Breast cancer patients who are positive for hormone receptor typically exhibit a favorable prognosis. It is controversial whether chemotherapy is necessary for them after surgery. Our study aimed to establish a multigene model to predict the relapse of hormone receptor-positive early-stage Chinese breast cancer after surgery and direct individualized application of chemotherapy in breast cancer patients after surgery. METHODS: In this study, differentially expressed genes (DEGs) were identified between relapse and nonrelapse breast cancer groups based on RNA sequencing. Gene set enrichment analysis (GSEA) was performed to identify potential relapse-relevant pathways. CIBERSORT and Microenvironment Cell Populations-counter algorithms were used to analyze immune infiltration. The least absolute shrinkage and selection operator (LASSO) regression, log-rank tests, and multiple Cox regression were performed to identify prognostic signatures. A predictive model was developed and validated based on Kaplan-Meier analysis, receiver operating characteristic curve (ROC). RESULTS: A total of 234 out of 487 patients were enrolled in this study, and 1588 DEGs were identified between the relapse and nonrelapse groups. GSEA results showed that immune-related pathways were enriched in the nonrelapse group, whereas cell cycle- and metabolism-relevant pathways were enriched in the relapse group. A predictive model was developed using three genes ( CKMT1B , SMR3B , and OR11M1P ) generated from the LASSO regression. The model stratified breast cancer patients into high- and low-risk subgroups with significantly different prognostic statuses, and our model was independent of other clinical factors. Time-dependent ROC showed high predictive performance of the model. CONCLUSIONS: A multigene model was established from RNA-sequencing data to direct risk classification and predict relapse of hormone receptor-positive breast cancer in Chinese patients. Utilization of the model could provide individualized evaluation of chemotherapy after surgery for breast cancer patients.

An overview of the correlation between IPI and prognosis in primary breast lymphoma.

Primary breast lymphoma (PBL), with diffuse large B-cell lymphoma (DLBCL) as the most histopathological type, is a rare disease with a poor prognosis. The International Prognostic Index (IPI) is an important clinical characteristic for risk stratification of PBL patients with different prognoses. However, the prognostic value of the IPI in PBL is controversial and needs to be refined. In this review, we described the clinical characteristics, pathogenesis, and treatment of PBL, with emphasis on the prognostic value of the IPI, its updated versions and IPIs for certain subtypes. A total of 9 types of IPIs were presented. In addition, the key issues with the various treatment modalities available were addressed, as well as the role of rituximab in therapy. We also summarized the current evidence and future challenges facing other types of prognostic indices. In particular, prospective clinical studies of treatment are rare, and the available data were mainly obtained from retrospective case series that included a small number of patients. Therefore, our conclusions and recommendations cannot serve as formal guidelines. However, this review attempts to provide an unbiased analysis of published data to provide clinicians with useful assistance in the treatment of this uncommon form of extranodal lymphoma.

Whole exome analysis reveals the genomic profiling related to chemo-resistance in Chinese population with limited-disease small cell lung cancer.

PURPOSE: The mechanism of chemo-resistance in small cell lung cancer (SCLC) is unclear. This study aims to explore the resistance-related genomic profiles of residual tumors after neo-adjuvant chemotherapy (NAC) in SCLC through the whole-exome sequencing (WES). EXPERIMENTAL DESIGN: A total of 416 limited diseases (LD) SCLC patients underwent surgery were retrospectively analyzed, of which 40 patients received NAC. Then we selected 29 patients undergoing NAC (n = 19) and chemotherapy naïve (CTN, n = 10) to perform WES sequence with formalin-fixed paraffin-embedded samples including tumor and paired para-tumor. RESULTS: In total, single nucleotide variation and mutation rate were similar between NAC and CTN groups. The mutation signatures were significantly discrepant between NAC and CTN groups, as well as among patients with partial response (PR), stable disease (SD), and progressive disease. There were more copy number variation deletions in NAC group compared with CTN group. The inactivation of TP53 and RB1 were the most significantly events in both NAC and CTN groups. RB1 nonsense mutations were recurrent in NAC group (9/19 vs. 0/9, 47.4% vs. 0%) with favorable survival, while the frame-shift deletions were frequent in CTN group (3/9 vs. 3/19, 33.3% vs.15.8%). Integrated function enrichment revealed that the frequently mutant genes were involved in cell cycle, metabolic reprogramming, and oncogenic signaling pathways in NAC group, such as BTG2 pathway, glycolysis in senescence and P53 pathway. A total of 27 genes presented frequently mutant in NAC group and might played a positive role in drug resistance. Multiple genes including BRINP3, MYH6, ST18, and PCHD15, which were associated with prognosis, occurred mutant frequently in PR and SD groups. CONCLUSION: Residual tumors after neo-adjuvant therapy exhibited different mutation signature spectrum. Multiple genes including RB1 nonsense mutations, BRINP3, MYH6, ST18, and PCHD15 were with frequent mutation in residual tumors, which might participate chemo-resistance and influenced the prognosis in patients with limited disease SCLC.

A 5-Pathway Signature Predicts Prognosis Based on Immune-Derived lncRNAs in Patients with Breast Cancer.

Background: Currently, predictive models were not developed based on the signaling pathway signatures of immune-related lncRNAs in breast cancer (BRCA) patients. Methods: We selected unsupervised hierarchical clustering algorithm to classify patients with BRCA based on the significant immune-derived lncRNAs from the TCGA dataset. And different methods including ESTIMATE, ImmuneCellAI, and CIBERSORT were performed to evaluate the immune infiltration of tumor microenvironment. Using Lasso regression algorithm, we filtered the significant signaling pathways enriched by GSEA, GSVA, or PPI analysis to develop a prognostic model. And a nomogram integrated with clinical factors and significant pathways was constructed to predict the precise probability of overall survival (OS) of BRCA patients in the TCGA dataset (n = 1,098) and another two testing sets (n = 415). Results: BRCA patients were stratified into the PC (n = 571) and GC (n = 527) subgroup with significantly different prognosis with 550 immune-related lncRNAs in the TCGA dataset. Integrated analysis revealed different immune response, oncogenic signaling, and metabolic reprograming pathways between these two subgroups. And a 5-pathway signature could predict the prognosis of BRCA patients between these two subgroups independently in the TCGA dataset, which was confirmed in another two cohorts from the GEO dataset. In the TCGA dataset, 5-year OS rate was 78% (95% CI: 73-84) vs. 82% (95% CI: 77-87) for the PC and GC group (HR = 1.63 (95% CI: 1.17-2.28), p = 0.004). The predictive power was similar in another two testing sets (HR > 1.20, p < 0.01). Finally, a nomogram is developed for clinical application, which integrated this signature and age to accurately predict the survival probability in BRCA patients. Conclusion: This 5-pathway signature correlated with immune-derived lncRNAs was able to precisely predict the prognosis for patients with BRCA and provided a rich source characterizing immune-related lncRNAs and further informed strategies to target BRCA vulnerabilities.

The prognostic value of IPI in patients with primary breast lymphoma, a multicenter retrospective study.

BACKGROUND: Due to the rarity of PBL and the lack of large-scale studies, the prognostic value of IPI in PBL was controversial. Especially in the rituximab era, the ability of IPI to stratify prognosis in patients receiving immunochemotherapy was severely reduced. Then revised IPI (R-IPI) and National Comprehensive Cancer Network IPI (NCCN-IPI) were introduced. The present study aimed to evaluate the prognostic value of IPI and the other IPIs in patients with PBL in a Chinese population. METHODS: We performed a multicenter retrospective study of 71 patients with PBL from 3 institutions in China. The Kaplan-Meier method and log-rank tests were used for the survival analysis. Cox regression analysis was performed to evaluate the prognostic factors. Subgroup analysis was performed to assess the prognostic significance of IPI scores, R-IPI scores, and NCCN-IPI scores. RESULTS: The median follow-up was 4.7 years (0.7-21.8 years). The 5-year progression-free survival (PFS) and overall survival (OS) rates were 90.2% and 96.3%. In the multivariate analysis, only IPI scores and radiotherapy were significantly associated with OS and PFS (P < 0.05). Applying the R-IPI in our patient cohort indicates a significant difference in PFS between the two groups of R-IPI (P = 0.034) but not for OS (P = 0.072). And the NCCN-IPI was prognostic for OS (P = 0.025) but not for PFS (P = 0.066). Subgroup analyses of IPI showed that survival analysis of IPI scores for the PFS and OS of patients using rituximab were not significantly different (P > 0.05). CONCLUSIONS: Our study confirms the prognostic value of IPI in patients with PBL, but the predictive value of IPI proved to be relatively low with the addition of the rituximab. The R-IPI and NCCN-IPI can accurately assess the high and low-risk groups of PBL patients but were insufficient to evaluate the intermediate risk group.

Ibrutinib-rituximab followed by R-HCVAD as frontline treatment for young patients (≤65 years) with mantle cell lymphoma (WINDOW-1): a single-arm, phase 2 trial.

BACKGROUND: Induction with ibrutinib and rituximab provides an opportunity to minimise chemotherapy exposure, because upfront use of these targeted therapies could result in remission without chemotherapy and allow for consolidation with only four cycles of chemotherapy instead of the conventional eight. We aimed to determine the activity and safety of ibrutinib-rituximab induction followed by shortened chemoimmunotherapy (four cycles) with rituximab plus hyper-fractionated cyclophosphamide, vincristine, doxorubicin, and dexamethasone (R-HCVAD) alternating with methotrexate-cytarabine in previously untreated patients with mantle cell lymphoma. METHODS: We did a single-centre, single-arm, phase 2 trial in previously untreated patients with mantle cell lymphoma. Eligible patients were aged 65 years or younger and had serum bilirubin of less than 1·5 mg/dL, creatinine clearance of 30 mL/min or more, Eastern Cooperative Oncology Group performance status of 2 or less, and cardiac ejection fraction 50% or more by echocardiogram. Patients received 12 cycles of ibrutinib-rituximab induction (part A; oral ibrutinib 560 mg daily and intravenous rituximab 375 mg/m2 weekly for the first 4 weeks and then on day 1 of cycles 3-12). As soon as patients had a complete response, four cycles of R-HCVAD alternating with methotrexate-cytarabine (part B) were administered. If they did not have a complete response or had a partial response, patients received two cycles of R-HCVAD alternating with methotrexate-cytarabine followed by reassessment, up to a total of eight cycles. Patients were taken off study if they had stable disease or progression during R-HCVAD. The primary outcome was the overall response rate after part A. The analyses were conducted on an intention-to-treat basis. This trial is registered with ClinicalTrials.gov, number NCT02427620. FINDINGS: 131 patients were enrolled between June 12, 2015, and Dec 6, 2018. The median age was 56 years (IQR 49-60). 58 (50%) of 117 patients had high Ki-67 (≥30%). 129 (98%, 95% CI 95-100) of 131 patients had an overall response in part A. The most common grade 3-4 adverse events were lymphocytopenia (19 [14%] of 131), skin rash (16 [12%]), thrombocytopenia (12 [9%]), infections (11 [8%]), and fatigue (ten [8%]) in part A and lymphocytopenia (96 [73%]), leukocytopenia (42 [32%]), thrombocytopenia (40 [30%]), and neutropenia (26 [20%]) in part B. There was one on-study death, which was not deemed to be treatment-related. INTERPRETATION: Induction with ibrutinib-rituximab in the frontline treatment of young patients with mantle cell lymphoma is active and safe. This approach allowed minimisation of the number of chemotherapy cycles, thereby reducing the adverse events associated with chemotherapy. Newer trials bringing the next-generation Bruton's tyrosine kinase inhibitors into the frontline setting might obviate the need for chemotherapy altogether in patients with mantle cell lymphoma. FUNDING: Pharmacyclics, Janssen.

Ibrutinib With Rituximab in First-Line Treatment of Older Patients With Mantle Cell Lymphoma.

PURPOSE: Most patients with mantle cell lymphoma (MCL) are older. In this study, we investigated the efficacy and safety of a chemotherapy-free combination with ibrutinib and rituximab (IR) in previously untreated older patients with MCL (age ≥ 65 years). METHODS: We enrolled 50 patients with MCL in this single-institution, single-arm, phase II clinical trial (NCT01880567). Patients with Ki-67% ≥ 50% and blastoid morphology were excluded. Ibrutinib was administered with rituximab up to 2 years with continuation of ibrutinib alone. The primary objective was to assess the overall response rate and safety of IR. In evaluable samples, whole-exome sequencing and bulk RNA sequencing from baseline tissue samples were performed. RESULTS: The median age was 71 years (interquartile range 69-76 years). Sixteen percent of patients had high-risk simplified MCL international prognostic index. The Ki-67% was low (< 30%) in 38 (76%) and moderately high (≥ 30%-50%) in 12 (24%) patients. The best overall response rate was 96% (71% complete response). After a median follow-up of 45 months (interquartile range 24-56 months), 28 (56%) patients came off study for various reasons (including four progression, 21 toxicities, and three miscellaneous reasons). The median progression-free survival and overall survival were not reached, and 3-year survival was 87% and 94%, respectively. None of the patients died on study therapy. Notably, 11 (22%) patients had grade 3 atrial fibrillation. Grade 3-4 myelosuppression was seen in < 5% of patients. Differential overexpression of CCND1, BIRC3, BANK1, SETBP1, AXIN2, and IL2RA was noted in partial responders compared with patients with complete response. CONCLUSION: IR combination is effective in older patients with MCL. Baseline evaluation for cardiovascular risks is highly recommended. Randomized trial is needed for definitive conclusions.

Cytotoxic lymphocytes-related gene ITK from a systematic CRISPR screen could predict prognosis of ovarian cancer patients with distant metastasis.

BACKGROUND: Ovarian cancer, a highly metastatic malignancy, has benefited tremendously from advances in modern human genomics. However, the genomic variations related to the metastasis remains unclear. METHODS: We filtered various significant genes (n = 6722) associated with metastasis within a large-scale functional genomic CRISPR/Cas9 knock-out library including 122,756 single guide RNAs, and identified ITK (IL2 Inducible T Cell Kinase) as a potential cancer suppressor gene for ovarian cancer metastasis. Downstream bioinformatic analysis was performed for ITK using public databases. RESULTS: We found that patients in low-ITK group had poor prognosis and more distant metastasis than those in high-ITK group in TCGA and GEO databases. We also demonstrated that ITK combined with the clinical factors could accurately predict prognosis through multiple Cox regression analysis and ROC analysis. Moreover, alterations correlated with distant metastasis emereged with significantly increased expression in SAMRCD1 in low-ITK group, but CD244 and SOCS1 in high-ITK group. Integrated analysis revealed dysregulated molecular processes including predominantly oncogenic signaling pathways in low-ITK group but immune related pathways in high-ITK group, which suggested ITK might inhibit distant metastasis in ovarian cancer. Furtherly, deconvolution of the cellular composition of all samples validated the close correlation between ITK and immune related function especially for cytotoxic lymphocytes. CONCLUSIONS: Together, these data provide insights into the potential role of ITK, with implications for the future development of tansformative ovarian cancer therapeutics.

9p21 loss confers a cold tumor immune microenvironment and primary resistance to immune checkpoint therapy.

Immune checkpoint therapy (ICT) provides substantial clinical benefits to cancer patients, but a large proportion of cancers do not respond to ICT. To date, the genomic underpinnings of primary resistance to ICT remain elusive. Here, we performed immunogenomic analysis of data from TCGA and clinical trials of anti-PD-1/PD-L1 therapy, with a particular focus on homozygous deletion of 9p21.3 (9p21 loss), one of the most frequent genomic defects occurring in ~13% of all cancers. We demonstrate that 9p21 loss confers "cold" tumor-immune phenotypes, characterized by reduced abundance of tumor-infiltrating leukocytes (TILs), particularly, T/B/NK cells, altered spatial TILs patterns, diminished immune cell trafficking/activation, decreased rate of PD-L1 positivity, along with activation of immunosuppressive signaling. Notably, patients with 9p21 loss exhibited significantly lower response rates to ICT and worse outcomes, which were corroborated in eight ICT trials of >1,000 patients. Further, 9p21 loss synergizes with PD-L1/TMB for patient stratification. A "response score" was derived by incorporating 9p21 loss, PD-L1 expression and TMB levels in pre-treatment tumors, which outperforms PD-L1, TMB, and their combination in identifying patients with high likelihood of achieving sustained response from otherwise non-responders. Moreover, we describe potential druggable targets in 9p21-loss tumors, which could be exploited to design rational therapeutic interventions.

Patient-derived cell lines and orthotopic mouse model of peritoneal carcinomatosis recapitulate molecular and phenotypic features of human gastric adenocarcinoma.

BACKGROUND: Gastric adenocarcinoma with peritoneal carcinomatosis (PC) is therapy resistant and leads to poor survival. To study PC in depth, there is an urgent need to develop representative PC-derived cell lines and metastatic models to study molecular mechanisms of PC and for preclinical screening of new therapies. METHODS: PC cell lines were developed from patient-derived PC cells. The tumorigenicity and metastatic potential were investigated by subcutaneously (PDXs) and orthotopically. Karyotyping, whole-exome sequencing, RNA-sequencing, and functional studies were performed to molecularly define the cell lines and compare genomic and phenotypic features of PDX and donor PC cells. RESULTS: We established three PC cell lines (GA0518, GA0804, and GA0825) and characterized them in vitro. The doubling times were 22, 39, and 37 h for GA0518, GA0804, and GA0825, respectively. Expression of cancer stem cell markers (CD44, ALDH1, CD133 and YAP1) and activation of oncogenes varied among the cell lines. All three PC cell lines formed PDXs. Interestingly, all three PC cell lines formed tumors in the patient derived orthotopic (PDO) model and GA0518 cell line consistently produced PC in mice. Moreover, PDXs recapitulated transcriptomic and phenotypic features of the donor PC cells. Finally, these cell lines were suitable for preclinical testing of chemotherapy and target agents in vitro and in vivo. CONCLUSION: We successfully established three patient-derived PC cell lines and an improved PDO model with high incidence of PC associated with malignant ascites. Thus, these cell lines and metastatic PDO model represent excellent resources for exploring metastatic mechanisms of PC in depth and for target drug screening and validation by interrogating GAC for translational studies.