The repertoire of copy number alteration signatures in human cancer.

Copy number alterations (CNAs) are a predominant source of genetic alterations in human cancer and play an important role in cancer progression. However comprehensive understanding of the mutational processes and signatures of CNA is still lacking. Here we developed a mechanism-agnostic method to categorize CNA based on various fragment properties, which reflect the consequences of mutagenic processes and can be extracted from different types of data, including whole genome sequencing (WGS) and single nucleotide polymorphism (SNP) array. The 14 signatures of CNA have been extracted from 2778 pan-cancer analysis of whole genomes WGS samples, and further validated with 10 851 the cancer genome atlas SNP array dataset. Novel patterns of CNA have been revealed through this study. The activities of some CNA signatures consistently predict cancer patients' prognosis. This study provides a repertoire for understanding the signatures of CNA in cancer, with potential implications for cancer prognosis, evolution and etiology.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer.

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Ovarian cancer cells regulate their mitochondrial content and high mitochondrial content is associated with a poor prognosis.

Most cancer patients ultimately die from the consequences of distant metastases. As metastasis formation consumes energy mitochondria play an important role during this process as they are the most important cellular organelle to synthesise the energy rich substrate ATP, which provides the necessary energy to enable distant metastasis formation. However, mitochondria are also important for the execution of apoptosis, a process which limits metastasis formation. We therefore wanted to investigate the mitochondrial content in ovarian cancer cells and link its presence to the patient's prognosis in order to analyse which of the two opposing functions of mitochondria dominates during the malignant progression of ovarian cancer. Monoclonal antibodies directed against different mitochondrial specific proteins, namely heat shock proteins 60 (HSP60), fumarase and succinic dehydrogenase, were used in immunohistochemistry in preliminary experiments to identify the antibody most suited to detect mitochondria in ovarian cancer cells in clinical tissue samples. The clearest staining pattern, which even delineated individual mitochondria, was seen with the anti-HSP60 antibody, which was used for the subsequent clinical study staining primary ovarian cancers (n = 155), borderline tumours (n = 24) and recurrent ovarian cancers (n = 26). The staining results were semi-quantitatively scored into three groups according to their mitochondrial content: low (n = 26), intermediate (n = 50) and high (n = 84). Survival analysis showed that high mitochondrial content correlated with a statistically significant overall reduced survival rate In addition to the clinical tissue samples, mitochondrial content was analysed in ovarian cancer cells grown in vitro (cell lines: OVCAR8, SKOV3, OVCAR3 and COV644) and in vivo in severe combined immunodeficiency (SCID) mice.In in vivo grown SKOV3 and OVCAR8 cells, the number of mitochondria positive cells was markedly down-regulated compared to the in vitro grown cells indicating that mitochondrial number is subject to regulatory processes. As high mitochondrial content is associated with a poor prognosis, the provision of high energy substrates by the mitochondria seems to be more important for metastasis formation than the inhibition of apoptotic cell death, which is also mediated by mitochondria. In vivo and in vitro grown human ovarian cancer cells showed that the mitochondrial content is highly adaptable to the growth condition of the cancer cells.

Analysis of the immune-inflammatory indices for patients with metastatic hormone-sensitive and castration-resistant prostate cancer.

BACKGROUND: Inflammation plays a pivotal role in the progression of prostate cancer (PCa). Several immune-inflammatory indices, including neutrophil to lymphocyte ratio (NLR), derived neutrophil to lymphocyte ratio (dNLR), lymphocyte to monocyte ratio (LMR) and platelet to lymphocyte ratio (PLR), lung immune prognostic index (LIPI), systemic inflammation response index (SIRI) and systemic immune inflammation index (SII), have demonstrated their prognostic values in several solid malignancies. However, Comparisons of superiority with these seven indices' predictive efficacy within metastatic hormone-sensitive PCa (mHSPC) and metastatic castration-resistant PCa (mCRPC) remain uncertain. METHODS: We retrospectively included 407 patients diagnosed with mHSPC and 158 patients with mCRPC at West China Hospital from 2005 to 2022. The seven immune-inflammatory indices were computed based on hematological data of mHSPC at initial diagnosis and mCRPC at progression to CRPC. Prognostic value for castration-resistant prostate cancer-free survival (CFS), overall survival (OS), prostate-specific antigen progression-free survival (PSA-PFS) and prostate-specific antigen (PSA) response was assessed using Kaplan-Meier curves, Cox regression models, and chi-square tests. The predictive performance of each immune-inflammatory index was assessed using the area under the curve (AUC) in time-dependent receiver operating characteristic curve (ROC) analysis and C-index calculation. RESULTS: All seven immune-inflammatory indices were significantly associated with CFS and OS in the mHSPC cohort, as well as with PSA response, PSA-PFS, and OS in the mCRPC cohort. In the mHSPC cohort, LIPI consistently exhibited higher AUC values compared to NLR, dNLR, LMR, PLR, SII, and SIRI for predicting CFS and OS. This indicates that LIPI had a superior discriminative ability compared to the other indices (C-index of LIPI: 0.643 and 0.686 for CFS and OS, respectively). Notably, the predictive advantage of LIPI over other indices in the mHSPC stage diminished in the mCRPC stage. CONCLUSIONS: This study firstly confirmed the prognostic value of SII, SIRI and LIPI in mHSPC and mCRPC, and revealed that LIPI had a higher predictive power than NLR, dNLR, LMR, PLR, SII and SIRI in mHSPC. These non-invasive indices can enable clinicians to quickly assess the prognosis of patients.

The Naples prognostic score serves as a predictor and prognostic indicator for cancer survivors in the community.

OBJECTIVE: Inflammation, malnutrition, and cancer are intricately interconnected. Despite this, only a few studies have delved into the relationship between inflammatory malnutrition and the risk of death among cancer survivors. This study aimed to specifically investigate the association between the categorically defined Naples prognostic score (NPS) and the prognosis of cancer survivors. METHODS: Data from 42,582 participants in the National Health and Nutrition Examination Survey (NHANES, 1999-2018) were subjected to analysis. Naples prognostic scores (NPS) were computed based on serum albumin (ALB), total cholesterol (TC), neutrophil to lymphocyte ratio (NLR), and lymphocyte to monocyte ratio (LMR), and participants were stratified into three groups accordingly. Cancer status was ascertained through a self-administered questionnaire, while mortality data were sourced from the National Death Index up to December 31, 2019. Multiple logistic regression was employed to estimate the odds ratio (OR) with a 95% confidence interval (CI) between NPS and cancer prevalence within the U.S. community population. Kaplan-Meier survival analysis and the Log-rank test were utilized to compare survival disparities among the three groups. Additionally, Cox proportional regression was utilized to estimate the hazard ratio (HR) with a 95% CI. RESULTS: The incidence of cancers was 9.86%. Among the participants, 8140 individuals (19.1%) were classified into Group 0 (NPS 0), 29,433 participants (69.1%) into Group 1 (NPS 1 or 2), and 5009 participants (11.8%) into Group 2 (NPS 3 or 4). After adjusting for confounding factors, the cancer prevalence for the highest NPS score yielded an odds ratio (OR) of 1.64 (95% CI: 1.36, 1.97) (P(for trend) < 0.05). In comparison to cancer survivors in Group 0, those with the highest NPS had adjusted hazard ratios (HRs) of 2.57 (95% CI: 1.73, 3.84) for all-cause mortality, 3.44 (95% CI: 1.64, 7.21) for cardiovascular mortality, 1.60 (95% CI: 1.01, 2.56) for cancer mortality, and 3.15 (95% CI: 1.74, 5.69) for other causes of mortality (All P(for trend) < 0.05). These associations remained consistent when stratified by age, sex, race, and body mass index. CONCLUSIONS: This study indicates that the Naples prognostic score (NPS), serving as a novel prognostic metric integrating inflammation and nutritional status, is closely linked to cancer prognosis within the general population.

Local augmented graph neural network for multi-omics cancer prognosis prediction and analysis.

Cancer prognosis prediction and analysis can help patients understand expected life and help clinicians provide correct therapeutic guidance. Thanks to the development of sequencing technology, multi-omics data, and biological networks have been used for cancer prognosis prediction. Besides, graph neural networks can simultaneously consider multi-omics features and molecular interactions in biological networks, becoming mainstream in cancer prognosis prediction and analysis. However, the limited number of neighboring genes in biological networks restricts the accuracy of graph neural networks. To solve this problem, a local augmented graph convolutional network named LAGProg is proposed in this paper for cancer prognosis prediction and analysis. The process follows: first, given a patient's multi-omics data features and biological network, the corresponding augmented conditional variational autoencoder generates features. Then, the generated augmented features and the original features are fed into a cancer prognosis prediction model to complete the cancer prognosis prediction task. The conditional variational autoencoder consists of two parts: encoder-decoder. In the encoding phase, an encoder learns the conditional distribution of the multi-omics data. As a generative model, a decoder takes the conditional distribution and the original feature as inputs to generate the enhanced features. The cancer prognosis prediction model consists of a two-layer graph convolutional neural network and a Cox proportional risk network. The Cox proportional risk network consists of fully connected layers. Extensive experiments on 15 real-world datasets from TCGA demonstrated the effectiveness and efficiency of the proposed method in predicting cancer prognosis. LAGProg improved the C-index values by an average of 8.5% over the state-of-the-art graph neural network method. Moreover, we confirmed that the local augmentation technique could enhance the model's ability to represent multi-omics features, improve the model's robustness to missing multi-omics features, and prevent the model's over-smoothing during training. Finally, based on genes identified through differential expression analysis, we discovered 13 prognostic markers highly associated with breast cancer, among which ten genes have been proved by literature review.

Can aggressive cancers be identified by the "aggressiveness" of their chromatin?

Phenotypic plasticity is a crucial feature of aggressive cancer, providing the means for cancer progression. Stochastic changes in tumor cell transcriptional programs increase the chances of survival under any condition. I hypothesize that unstable chromatin permits stochastic transitions between transcriptional programs in aggressive cancers and supports non-genetic heterogeneity of tumor cells as a basis for their adaptability. I present a mechanistic model for unstable chromatin which includes destabilized nucleosomes, mobile chromatin fibers and random enhancer-promoter contacts, resulting in stochastic transcription. I suggest potential markers for "unsettled" chromatin in tumors associated with poor prognosis. Although many of the characteristics of unstable chromatin have been described, they were mostly used to explain changes in the transcription of individual genes. I discuss approaches to evaluate the role of unstable chromatin in non-genetic tumor cell heterogeneity and suggest using the degree of chromatin instability and transcriptional noise in tumor cells to predict cancer aggressiveness.

Impact of preoperative haemoglobin, albumin, lymphocyte, and platelet score on oral cancer prognosis.

OBJECTIVE: To evaluate the preoperative haemoglobin, albumin, lymphocyte, and platelet score as a prognostic indicator in oral squamous cell carcinoma treated by radical surgery. SUBJECTS AND METHODS: Patients (83 men, 32 women; 65.80 ± 11.47 years) who underwent radical surgery between 2012 and 2022 were included. Factors affecting overall survival and disease-free survival according to the haemoglobin, albumin, lymphocyte, and platelet score were examined. Patients were categorised into low- and high-score groups using optimal cut-off values obtained from receiver operating characteristic curve analysis. RESULTS: The low-score group had poorer overall and disease-free survival (p < 0.001 each). Multivariate analysis identified alcohol consumption (hazard ratio [HR], 3.83; 95% confidence interval [CI]: 1.56-9.41, p = 0.003); vascular invasion (HR, 3.97; 95% CI: 1.60-9.85, p = 0.003); and the haemoglobin, albumin, lymphocyte, and platelet score (HR, 0.39; 95% CI: 0.20-0.78, p = 0.007) as independent prognostic factors for overall survival and vascular (HR, 3.66; 95% CI: 1.79-7.50, p < 0.001) and lymphovascular (HR, 2.44; 95% CI: 1.36-4.41, p = 0.003) invasion as independent prognostic factors for disease-free survival. CONCLUSION: The preoperative haemoglobin, albumin, lymphocyte, and platelet score may be a significant prognostic factor for patients with oral squamous cell carcinoma undergoing radical surgery.

Comprehensive prognostic assessment in kidney cancer: A multidimensional approach analyzing Fufang Sanling granules, genetic variants, and immune infiltration.

This study delves into the potential therapeutic benefits of Fufang Sanling Granules for kidney cancer, focusing on their active components and the underlying mechanisms of their interaction with cancer-related targets. By constructing a drug-active component-target network based on eight herbs, key active compounds such as kaempferol, quercetin, and linolenic acid were identified, suggesting their pivotal roles in modulating immune responses and cellular signaling pathways relevant to cancer progression. The research further identified 51 central drug-disease genes through comprehensive bioinformatics analyses, implicating their involvement in crucial biological processes and pathways. A novel risk score model, encompassing six genes with significant prognostic value for renal cancer, was established and validated, showcasing its effectiveness in predicting patient outcomes through mutation analysis and survival studies. The model's predictive power was further confirmed by its ability to stratify patients into distinct risk groups with significant survival differences, highlighting its potential as a prognostic tool. Additionally, the study explored the relationship between gene expression within the identified black module and the risk score, uncovering significant associations with the extracellular matrix and immune infiltration patterns. This reveals the complex interplay between the tumor microenvironment and cancer progression. The integration of the risk score with clinical parameters through a nomogram significantly improved the model's predictive accuracy, offering a more comprehensive tool for predicting kidney cancer prognosis. In summary, by combining detailed molecular analyses with clinical insights, this study presents a robust framework for understanding the therapeutic potential of Fufang Sanling Granules in kidney cancer. It not only sheds light on the active components and their interactions with cancer-related genes but also introduces a reliable risk score model, paving the way for personalized treatment strategies and improved patient management in the future.

Prognostic Value of B7H4 Expression in Patients with Solid Cancers: A Systematic Review and Meta-Analysis.

V-set domain-containing T-cell activation inhibitor 1 (aliases VTCN1, B7H4) participates in tumour immune escape by delivering inhibitory signals to T cells. The purpose of this article was to assess the B7H4 prognostic value in solid cancers. Three databases were searched for relevant articles. The main endpoints were overall survival (OS), disease-specific survival (DSS), progression-free survival (PFS), recurrence-free survival (RFS), and disease-free survival (DFS). Appropriate hazard ratios (HRs) were pooled. The R studio software (version 4.0.3) was used for data analysis. Thirty-one studies met the inclusion criteria. High expression of B7H4 was associated with worse OS (HR = 1.52, 95% CI: 1.37-1.68) but not with DSS (HR = 1.14, 95% CI: 0.49-2.63), RFS (HR = 1.77, 95% CI: 0.75-4.18), DFS (HR = 1.29, 95% CI: 0.8-2.09), or PFS (HR = 1.71, 95% CI: 0.91-3.2) in patients with solid cancers. High expression of B7H4 is associated with a poorer prognosis in patients with solid cancers. B7H4 is a promising prognostic biomarker and immunotherapeutic target for various solid cancers because of its activity in cancer immunity and tumourigenesis.

Exploring the Immunological Profile in Breast Cancer: Recent Advances in Diagnosis and Prognosis through Circulating Tumor Cells.

This review offers a comprehensive exploration of the intricate immunological landscape of breast cancer (BC), focusing on recent advances in diagnosis and prognosis through the analysis of circulating tumor cells (CTCs). Positioned within the broader context of BC research, it underscores the pivotal role of the immune system in shaping the disease's progression. The primary objective of this investigation is to synthesize current knowledge on the immunological aspects of BC, with a particular emphasis on the diagnostic and prognostic potential offered by CTCs. This review adopts a thorough examination of the relevant literature, incorporating recent breakthroughs in the field. The methodology section succinctly outlines the approach, with a specific focus on CTC analysis and its implications for BC diagnosis and prognosis. Through this review, insights into the dynamic interplay between the immune system and BC are highlighted, with a specific emphasis on the role of CTCs in advancing diagnostic methodologies and refining prognostic assessments. Furthermore, this review presents objective and substantiated results, contributing to a deeper understanding of the immunological complexity in BC. In conclusion, this investigation underscores the significance of exploring the immunological profile of BC patients, providing valuable insights into novel advances in diagnosis and prognosis through the utilization of CTCs. The objective presentation of findings emphasizes the crucial role of the immune system in BC dynamics, thereby opening avenues for enhanced clinical management strategies.

[Factors affecting the postoperative prognosis of penile cancer].

OBJECTIVE: To investigate the risk factors affecting the prognosis of penile cancer after surgery. METHODS: We retrospectively analyzed the clinical data on 112 cases of penile cancer treated in Weifang People's Hospital from January 2013 to December 2023. Using the Kaplan-Meier survival curve, χ2 test, Fisher's exact test, and univariate and multivariate Cox risk regression analyses, we compared the clinical characteristics among different groups, and determined the independent prognostic risk factors for cancer-specific survival (CSS) of the patients. RESULTS: The 1-, 3- and 5-year CSS rates of the penile cancer patients were 78.2%, 66.1% and 63.7%, respectively. Kaplan-Meier analysis indicated a significant correlation of a higher neutrophil-to-lymphocyte ratio (NLR) with a lower CSS rate (P < 0.001). Multivariate Cox regression analysis showed high NLR (HR = 2.6; 95% CI: 1.031－6.558; P = 0.043) to be an independent risk factor for CSS. CONCLUSION: Preoperative NLR is an independent risk factor for the prognosis of penile cancer. In addition, older age, farmer or worker occupation, lower education, preoperative lymphocyte-to-monocyte ratio (LMR)≤2.81, preoperative fibrinogen (FIB)≥3.41 g/L, advanced tumor stage and tumor differentiation are associated with the poor prognosis the malignancy.

Germline genetic variability in pancreatic cancer risk and prognosis.

Pancreatic cancer (PC), particularly its most common form, pancreatic ductal adenocarcinoma (PDAC), is relatively rare but highly lethal. Knowledge about PC risk factors could in the long term contribute to early diagnosis and mortality reduction. We review the current status of research on germline genetic factors for PC risk. Genome-wide association studies (GWAS) successfully identified common loci convincingly associated with PC risk, an endeavor that is still ongoing. The function of only a handful of risk loci has being thoroughly characterized so far. Secondary analyses of existing GWAS data are being used to discover novel loci. GWAS data have also been used to study additional risk factors with a Mendelian randomization approach. Polygenic/multifactorial risk scores show much larger risks than individual variants, but their use for risk stratification in the population is not warranted yet. At the other end of the spectrum of inherited PC risk factors, rare high-penetrance variants co-segregating with the disease have been observed in familial cancer syndromes that include PC, or in families with multiple recurrence of PC alone. Rare variants predicted to have a deleterious effect on function are studied also with a case-control approach, by resequencing candidate genes or whole-exomes/whole-genomes. Telomere length and mitochondrial DNA copy number are useful additional DNA-based markers of PC susceptibility. The role of common variants in prognosis of PC patients has also been explored, albeit with more limited success than risk. Finally, genetics of pancreatic neuroendocrine tumors (PNET), a rarer and heterogeneous form of PC, is still understudied.

Immune functions as a ligand or a receptor, cancer prognosis potential, clinical implication of VISTA in cancer immunotherapy.

Since cancer immunotherapy with immune checkpoint inhibitors of PD/PDL-1 and CTLA-4 limited efficacy to the patients due to resistance during the current decade, novel target is required for customized treatment due to tumor heterogeneity. V-domain Ig-containing suppressor of T cell activation (VISTA), a programmed death protein-1(PD-1) homolog expressed on T cells and on antigen presenting cells(APC), has emerged as a new target in several cancers. Though VISTA inhibitors including CA-170 are considered attractive in cancer immunotherapy to date, the information on VISTA as a potent biomarker of cancer prognosis and its combination therapy is still lacking to date. Thus, in this review, we discussed extracellular domain, ligands, expression, immune functions and clinical implications of VISTA and finally suggested conclusion and perspectives.

Reigniting hope in cancer treatment: the promise and pitfalls of IL-2 and IL-2R targeting strategies.

Interleukin-2 (IL-2) and its receptor (IL-2R) are essential in orchestrating immune responses. Their function and expression in the tumor microenvironment make them attractive targets for immunotherapy, leading to the development of IL-2/IL-2R-targeted therapeutic strategies. However, the dynamic interplay between IL-2/IL-2R and various immune cells and their dual roles in promoting immune activation and tolerance presents a complex landscape for clinical exploitation. This review discusses the pivotal roles of IL-2 and IL-2R in tumorigenesis, shedding light on their potential as diagnostic and prognostic markers and their therapeutic manipulation in cancer. It underlines the necessity to balance the anti-tumor activity with regulatory T-cell expansion and evaluates strategies such as dose optimization and selective targeting for enhanced therapeutic effectiveness. The article explores recent advancements in the field, including developing genetically engineered IL-2 variants, combining IL-2/IL-2R-targeted therapies with other cancer treatments, and the potential benefits of a multidimensional approach integrating molecular profiling, immunological analyses, and clinical data. The review concludes that a deeper understanding of IL-2/IL-2R interactions within the tumor microenvironment is crucial for realizing the full potential of IL-2-based therapies, heralding the promise of improved outcomes for cancer patients.

Genome-wide study of genetic polymorphisms predictive for outcome from first-line oxaliplatin-based chemotherapy in colorectal cancer patients.

We conducted the first large genome-wide association study to identify novel genetic variants that predict better (or poorer) prognosis in colorectal cancer patients receiving standard first-line oxaliplatin-based chemotherapy vs chemotherapy without oxaliplatin. We used data from two phase III trials, NCCTG N0147 and NCCTG N9741 and a population-based patient cohort, DACHS. Multivariable Cox proportional hazards models were employed, including an interaction term between each SNP and type of treatment for overall survival (OS) and progression-free survival. The analysis was performed for studies individually, and the results were combined using fixed-effect meta-analyses separately for resected stage III colon cancer (3098 patients from NCCTG N0147 and 549 patients from DACHS) and mCRC (505 patients from NCCTG N9741 and 437 patients from DACHS). We further performed gene-based analysis as well as in silico bioinformatics analysis for CRC-relevant functional genomic annotation of identified loci. In stage III colon cancer patients, a locus on chr22 (rs11912167) was associated with significantly poorer OS after oxaliplatin-based chemotherapy vs chemotherapy without oxaliplatin (Pinteraction < 5 × 10-8 ). For mCRC patients, three loci on chr1 (rs1234556), chr12 (rs11052270) and chr15 (rs11858406) were found to be associated with differential OS (P < 5 × 10-7 ). The locus on chr1 located in the intronic region of RCSD1 was replicated in an independent cohort of 586 mCRC patients from ALGB/SWOG 80405 (Pinteraction = .04). The GWA gene-based analysis yielded for RCSD1 the most significant association with differential OS in mCRC (P = 6.6 × 10-6 ). With further investigation into its biological mechanisms, this finding could potentially be used to individualize first-line treatment and improve clinical outcomes.

Prognostic impact of germline BRCA1/2 pathogenic variants in breast cancer.

PURPOSE: This study investigates the impact of different subtypes of pathogenic BRCA variants on the prognosis and on the survival of breast cancer (BC) patients. METHODS: Associations between BRCA1/2 pathogenic variants (PVs) mutations, clinicopathological features, locoregional tumor reappearance, and survival data were analyzed. The Gray's test was used to test difference of the cumulative incidence of local relapse between missense/splicing and other mutations, taking into of competing events. The multivariate proportional hazard model was used to assess the independent association between type of mutation and local relapse, after adjustment for other prognostic factors and clinicopathological characteristics. RESULTS: Out of 482 patients, 285 presented 98 different BRCA1 PVs and 201 harbored 103 different BRCA2 PVs. Missense mutations were found in 46 BC patients (9.5%), splicing mutations in 42 (8.6%), deletions in 206 (42.4%), insertions in 73 (15%), indel mutations in 6 (1.2%), nonsense mutations in 86 (17.7%), and large rearrangements in 27 (5.6%). Kalbfleisch and Prentice cumulative incidence curves analysis showed a significantly lower locoregional recurrence incidence in the missense/splicing group (Gray-test P-value = 0.011). We found that the risk of local relapse was 58% less likely in women carrying missense/splicing variants than in those with other PV subtypes (HR 95% CI 0.42 [0.21-0.82]; P-value = 0.0108). No significant differences were observed in overall survival (OS) in all groups. CONCLUSIONS: Having been found to be associated with a lower risk of BC reappearance, germline BRCA1/2 PVs of the missense/splicing subtypes can be used as prognostic predictors and are likely to improve BC patients' management.

Ovarian removal and subsequent breast cancer prognosis: a nationwide cohort study.

PURPOSE: To evaluate whether previous ovarian removal concomitant with benign hysterectomy improves prognosis in a cohort of women with breast cancer. METHODS: In this nationwide register-based cohort study, risk of recurrence and mortality were examined in 4563 women with invasive breast cancer and previous bilateral salpingo-oophorectomy (BSO) concomitant with benign hysterectomy, during 1977-2018. Comparing with benign hysterectomy alone, hazard ratios (HRs) and 95% confidence intervals (CIs) were evaluated by Cox-proportional hazards regression models. Analyses were stratified on age at hysterectomy as a proxy for menopausal status (< 45, 45-54 and ≥ 55 years); tumor characteristics, estrogen receptor (ER)-status, and use of hormone therapy (HT) were included in multivariable models. RESULTS: Compared with hysterectomy alone, premenopausal (< 45 years) BSO at benign hysterectomy was associated with an age and calendar period adjusted HR of 1.48 (95% CI 0.83-2.65) for breast cancer recurrence within 10 years of follow-up, a HR of 1.07 (95% CI 0.66-1.72) for overall mortality after breast cancer, and a HR of 0.59 (95% CI 0.26-1.32) for breast cancer-specific mortality. The corresponding HRs for postmenopausal (≥ 55 years) BSO at benign hysterectomy were 1.51 (95% CI 0.73-3.12) for recurrences, 1.34 (95% CI 0.74-2.44) for overall mortality, and 1.78 (95% CI 0.74-4.30) for breast cancer mortality. Adjusting for tumor characteristics, ER-status and HT did not alter the results. CONCLUSION: Results from this cohort study did not indicate an improvement in breast cancer prognosis when removing the ovaries at benign hysterectomy prior to the cancer diagnosis.

Application of radiomics-based multiomics combinations in the tumor microenvironment and cancer prognosis.

The advent of immunotherapy, a groundbreaking advancement in cancer treatment, has given rise to the prominence of the tumor microenvironment (TME) as a critical area of research. The clinical implications of an improved understanding of the TME are significant and far-reaching. Radiomics has been increasingly utilized in the comprehensive assessment of the TME and cancer prognosis. Similarly, the advancement of pathomics, which is based on pathological images, can offer additional insights into the panoramic view and microscopic information of tumors. The combination of pathomics and radiomics has revolutionized the concept of a "digital biopsy". As genomics and transcriptomics continue to evolve, integrating radiomics with genomic and transcriptomic datasets can offer further insights into tumor and microenvironment heterogeneity and establish correlations with biological significance. Therefore, the synergistic analysis of digital image features (radiomics, pathomics) and genetic phenotypes (genomics) can comprehensively decode and characterize the heterogeneity of the TME as well as predict cancer prognosis. This review presents a comprehensive summary of the research on important radiomics biomarkers for predicting the TME, emphasizing the interplay between radiomics, genomics, transcriptomics, and pathomics, as well as the application of multiomics in decoding the TME and predicting cancer prognosis. Finally, we discuss the challenges and opportunities in multiomics research. In conclusion, this review highlights the crucial role of radiomics and multiomics associations in the assessment of the TME and cancer prognosis. The combined analysis of radiomics, pathomics, genomics, and transcriptomics is a promising research direction with substantial research significance and value for comprehensive TME evaluation and cancer prognosis assessment.

Effect of celecoxib plus standard chemotherapy on cancer prognosis: A systematic review and meta-analysis.

BACKGROUND: Inflammation is closely related to cancer prognosis. The effect of celecoxib, a nonsteroidal anti-inflammatory drug, on the prognosis of patients with cancer remains uncertain. To assess the association between celecoxib plus standard chemotherapy and cancer prognosis, we conducted a systematic review and meta-analysis of published studies. METHODS: PubMed, EMBASE, and the Cochrane Library were searched from inception until July 2022 for randomized controlled trials reporting the prognosis of patients with cancer treated with celecoxib plus standard chemotherapy. The primary endpoints were overall survival (OS) and progression-free survival (PFS). Meta-analysis was performed using Review Manager software version 5.4. The following search terms were used in the databases: ((((celecoxib)) AND ((((((((cancer) OR (carcinoma)) OR (sarcoma)) OR (neoplasms)) OR (tumor)) OR (tumour)) OR (tumors)) OR (tumours))) AND ((survival) OR (mortality))) AND (((Clinical Trials, Randomized) OR (Trials, Randomized Clinical)) OR (Controlled Clinical Trials, Randomized)). RESULTS: Overall, 13 randomized controlled trials, including 8957 patients with cancer, were included in the analysis. Compared to conventional chemotherapy alone, 1-year OS and 1-year PFS rates were not significantly improved with celecoxib adjuvant therapy (OS: p = .38; PFS: p = .65). In addition, no differences were observed between the celecoxib and placebo groups in 3-year overall (p = .98), 3-year progression-free (p = .40), 5-year overall (p = .59), or 5-year progression-free (p = .56) survival rates. An increase in the risk ratio of leukopenia (p = .02) and thrombocytopenia (p = .05) was also observed, suggesting that celecoxib promotes hematologic toxicity. No increased risk of cardiovascular (p = .96) and gastrointestinal (p = .10-.91) events was observed. CONCLUSIONS: The addition of celecoxib to standard chemotherapy did not improve OS or PFS rates of patients with cancer. Additionally, celecoxib can increase hematologic toxicity without increasing the risk of gastrointestinal or cardiovascular reactions. Further randomized controlled trials are necessary to clarify its effects and applications.