Types Of Cancer Research Articles

A Probabilistic Approach to Estimate the Temporal Order of Pathway Mutations Accounting for Intra-Tumor Heterogeneity.

The development of cancer involves the accumulation of somatic mutations in several essential biological pathways. Delineating the temporal order of pathway mutations during tumorigenesis is crucial for comprehending the biological mechanisms underlying cancer development and identifying potential targets for therapeutic intervention. Several computational and statistical methods have been introduced for estimating the order of somatic mutations based on mutation profile data from a cohort of patients. However, one major issue of current methods is that they do not take into account intra-tumor heterogeneity (ITH), which limits their ability to accurately discern the order of pathway mutations. To address this problem, we propose PATOPAI, a probabilistic approach to estimate the temporal order of mutations at the pathway level by incorporating ITH information as well as pathway and functional annotation information of mutations. PATOPAI uses a maximum likelihood approach to estimate the probability of pathway mutational events occurring in a specific sequence, wherein it focuses on the orders that are consistent with the phylogenetic structure of the tumors. Applications to whole exome sequencing data from The Cancer Genome Atlas (TCGA) illustrate our method's ability to recover the temporal order of pathway mutations in several cancer types.

RAbDesFlow: A novel workflow for computational recombinant antibody design for healthcare engineering

Abstract Background Recombinant antibodies have emerged as a promising solution to tackle antigen specificity, enhancement of immunogenic potential and versatile functionalization to treat human diseases. The development of single chain variable fragments (scFv) has helped accelerate treatment in cancers and viral infections, due to their favorable pharmacokinetics and human compatibility. However, designing recombinant antibodies is traditionally viewed as a genetic engineering problem, with phage display and cell free systems playing a major role in sequence selection for gene synthesis. The process of antibody engineering involves complex and time-consuming laboratory techniques, which demand substantial resources and expertise. The success rate of obtaining desired antibody candidates through experimental approaches can be modest, necessitating iterative cycles of selection and optimization. With ongoing advancements in technology, in silico design of diverse antibody libraries, screening and identification of potential candidates for in vitro validation can be accelerated. Methods To meet this need, we have developed rAbDesFlow, a unified computational workflow for recombinant antibody engineering with open-source programs and tools for ease of implementation. Results The workflow encompasses five computational modules to perform antigen selection, antibody library generation, antigen and antibody structure modeling, antigen-antibody interaction modeling, structure analysis, and consensus ranking of potential antibody sequences for synthesis and experimental validation. The proposed workflow has been demonstrated through design of recombinant antibodies for the ovarian cancer antigen Mucin-16 (CA-125). Conclusions This approach can serve as a blueprint for designing similar engineered molecules targeting other biomarkers, allowing for a simplified adaptation to different cancer types or disease-specific antigens.

The roles of tertiary lymphoid structures in genitourinary cancers: a comprehensive review of current advances and clinical applications.

The presence of tertiary lymphoid structures (TLSs) associated with distinct treatment efficacy and clinical prognosis has been identified in various cancer types. However, the mechanistic roles and clinical implications of TLSs in genitourinary (GU) cancers remain incompletely explored. Despite their potential role as predictive marker described in numerous studies, it is essential to comprehensively evaluate the characteristics of TLSs, including drivers of formation, structural foundation, cellular compositions, maturation stages, molecular features, and specific functionality to maximize their positive impacts on tumor-specific immunity. The unique contributions of these structures to cancer progression and biology have fueled interest in these structures as mediators of antitumor immunity. Emerging data are trying to explore the effects of therapeutic interventions targeting TLSs. Therefore, a better understanding of the molecular and phenotypic heterogeneity of TLSs may facilitate the development of TLSs-targeting therapeutic strategies to obtain optimal clinical benefits for GU cancers in the setting of immunotherapy. In this review, we focus on the phenotypic and functional heterogeneity of TLSs in cancer progression, current therapeutic interventions targeting TLSs and the clinical implications and therapeutic potential of TLSs in GU cancers.

Increased risk of subsequent primary lung cancer among female hormone-related cancer patients: A meta-analysis based on over four million cases.

The incidence rate of lung cancer in women has significantly increased over the past decade, and previous evidence has indicated a significant relationship between the elevated levels of sex hormones and the risk of lung cancer. Therefore, we hypothesized that female hormone-related cancer (FHRC) patients, including breast, endometrial, cervical, and ovarian cancer patients, may experience a higher risk of developing subsequent lung cancer. This meta-analysis aimed to identify the risk of lung cancer among FHRC patients compared to the general population. The PubMed, Web of Science, EMBASE, Cochrane Library, and CNKI databases were searched up to May 11, 2022. Standardized incidence ratios (SIRs) with 95% confidence intervals (CIs) were used to identify the risk of subsequent lung cancer after FHRC. Subgroup analyses based on the follow-up time and tumor type were also conducted. A total of 58 retrospective cohort studies involving 4,360,723 FHRC participants were included. The pooled results demonstrated that FHRC patients had a significantly increased risk of developing subsequent primary lung cancer (SIR=1.61, 95% CI: 1.48-1.76, P <0.001). Subgroup analysis revealed an obvious trend of increasing lung cancer risk over time (SIRs for <5years, ≥5years, ≥10years, ≥20years, and ≥30years after FHRC: 1.32, 1.59, 1.57, 1.68, and 1.95, respectively). In addition, subgroup analysis stratified by tumor type indicated an increased risk of developing subsequent lung cancer after breast (SIR=1.25, P <0.001), endometrial (SIR=1.40, P =0.019), cervical (SIR=2.56, P <0.001), and ovarian cancer (SIR=1.50, P =0.010). FHRC patients are more likely to develop lung cancer than the general population. Furthermore, the increased risk of subsequent primary lung cancer is more obvious with a longer survival time and is observed in all types of hormone-related cancer. International Platform of Registered Systematic Review and Meta-analysis Protocols: No. INPLASY202270044; https://inplasy.com/.

Real world results of locally advanced and metastatic lung cancer patients treated with platinum doublet chemotherapy in first line: Moroccan cohort

BackgroundDoublet platin-chemotherapy was the old standard treatment for different histology types of advanced and metastatic lung cancer (LC) and is still an option for patients who are not eligible for immune checkpoint inhibitors. However, in low- and middle-income countries, chemotherapy, either in monotherapy or in combination with platinum, is still the only accessible option in public institutions. The efficacy of different platin-based chemotherapy in patients with LC who are treatment-naïve is unknown. MethodsIn this retrospective study, we selected patients with advanced and metastatic (IIIB-IVB) non-squamous non-small cell LC (NSCLC), squamous NSCLC, and lung neuroendocrine tumours (small cell LC (SCLC), large cell neuroendocrine, and atypical carcinoid) aged beyond 18 years who received first-line chemotherapy (docetaxel, gemcitabine, etoposide, paclitaxel, pemetrexed, and vinorelbine) combined with platinum between January 1, 2013, and December 31, 2022. Within the population with non-squamous NSCLC, squamous NSCLC, and neuroendocrine tumours, progression-free survival (PFS) and overall survival (OS) were the primary assessed endpoints. Hematologic safety was the secondary endpoint. ResultsOverall, 611 patients were included. In the group of patients with non-squamous NSCLC (n = 390), there was no statistical difference between subgroups of patients who received first-line platin-chemotherapy. The median PFS was 182 (95 % confidence interval [CI], 167–208) days (hazard ratio for progression: NR [Not Reached]; p = 0.37), and the median OS was 446 (95 % CI, 405–559) days (hazard ratio for death: 1.31; 95 % CI, 0.94 - 1.82; p = 0.1). In the group of patients with squamous NSCLC (n = 149), we note the absence of statistical significance between subgroups of patients who received platin-based chemotherapy. The median PFS was 195 (95 % CI, 142–238; hazard ratio for progression: 1.21, 95 % CI, 0.29–5.02; p = 0.27), while the median OS was 428 (95 % CI, 324–940) days (hazard ratio for death: 1.76; 95 % CI, 0.93 to 3.3; p = 0.32). The absence of significance has been noticed in the neuroendocrine subgroup of patients who received first etoposide-platinum, vinorelbine-platinum, or paclitaxel-platinum (n = 72). The median PFS was 216 (95 % CI, 193–277) days; hazard ratio for progression: 1.74, 95 % CI, 0.41–7.27; p = 0.69, while the median OS was 273 (95 % CI, 241–459) days (hazard ratio for death: 2.95; 95 % CI, 0.4–21.7; p = 0.51). Grade 3–4 neutropenia grade was the predominant adverse event associated with chemotherapy in almost 11 % of patients. ConclusionMoving forward, treatment strategies must be refined for patients, with an emphasis on increasing the number of patients who can benefit from emergent approaches in order to guarantee a wider, deeper, and longer-lasting outcome.

Deep learning for lungs cancer detection: a review

Although lung cancer has been recognized to be the deadliest type of cancer, a good prognosis and efficient treatment depend on early detection. Medical practitioners’ burden is reduced by deep learning techniques, especially Deep Convolutional Neural Networks (DCNN), which are essential in automating the diagnosis and classification of diseases. In this study, we use a variety of medical imaging modalities, including X-rays, WSI, CT scans, and MRI, to thoroughly investigate the use of deep learning techniques in the field of lung cancer diagnosis and classification. This study conducts a comprehensive Systematic Literature Review (SLR) using deep learning techniques for lung cancer research, providing a comprehensive overview of the methodology, cutting-edge developments, quality assessments, and customized deep learning approaches. It presents data from reputable journals and concentrates on the years 2015–2024. Deep learning techniques solve the difficulty of manually identifying and selecting abstract features from lung cancer images. This study includes a wide range of deep learning methods for classifying lung cancer but focuses especially on the most popular method, the Convolutional Neural Network (CNN). CNN can achieve maximum accuracy because of its multi-layer structure, automatic learning of weights, and capacity to communicate local weights. Various algorithms are shown with performance measures like precision, accuracy, specificity, sensitivity, and AUC; CNN consistently shows the greatest accuracy. The findings highlight the important contributions of DCNN in improving lung cancer detection and classification, making them an invaluable resource for researchers looking to gain a greater knowledge of deep learning’s function in medical applications.

Long-Term Outcomes of the Treatment for Gastric Tube Cancer After Esophagectomy for Esophageal Cancer.

The long-term outcomes of gastric tube cancer (GTC) are unclear. This study therefore aimed to clarify clinicopathologic features and the long-term outcomes of patients with GTC. The 25 patients who were diagnosed with GTC between April 2003 and December 2022 at our hospital were eligible for inclusion in this retrospective study, and this included 27 lesions. We retrospectively evaluated clinicopathologic factors based on hospital records. In our cohort, 88% of incidences of GTC were located in the middle or lower gastric tube. As the treatment of GTC, we used endoscopic submucosal dissection, gastrectomy, chemoradiotherapy, chemotherapy, and best supportive care for 16 (59%), 6 (22%), 1 (4%), 1 (4%), and 3 (11%) lesions, respectively. Perforation after endoscopic submucosal dissection was observed in 6 of the 16 lesions. Partial gastric tube resection was performed for 3 patients and total gastric tube resection was performed for 3 patients. One patient who underwent total gastric tube resection died due to acute respiratory distress syndrome. In survival analysis, the 3-year overall survival rate was 52% and the 3-year disease-specific survival rate was 74%. Five patients (20%) died of aspiration pneumonia, 2 patients (8%) of another disease, and 1 patient (4%) of another type of cancer. According to multivariate analysis, independent prognostic factors for overall survival were cN status (HR, 18.021; P=0.004) and complication of aspiration pneumonia (HR, 8.373; P=0.004). The occurrence of aspiration pneumonia and cN status were prognostic factors after the treatment for GTC. Assessment of dysphagia and surveillance after treatment for GTC are important to improve the prognosis.

Pantoprazole and riluzole target H+/K+-ATPases and pH-sensitive K+ channels in pancreatic cancer cells.

Pancreatic ductal adenocarcinoma (PDAC) remains the most lethal cancer type. PDAC is characterized by fibrotic, hypoxic, and presumably acidic tumor microenvironment (TME). Acidic TME is an important player in tumor development, progression, aggressiveness, and chemoresistance. The dysregulation of ductal ion transporters/channels might contribute to extracellular pH (pHe) acidification and PDAC progression. Our aim was to test whether H+/K+-ATPases and pH-sensitive K+ channels contribute to these processes and could be targeted by clinically approved drugs. We used human pancreatic cancer cells adapted to various pHe conditions and grown in monolayers and spheroids. First, we created cells expressing pHoran4 at the outer plasma membrane and showed that pantoprazole, the H+/K+-ATPase inhibitor, alkalinized pHe. Second, we used FluoVolt to monitor the membrane voltage (Vm) and showed that riluzole hyperpolarized Vm, most likely by opening of pH-sensitive K+ channels such as TREK-1. Third, we show that pantoprazole and riluzole inhibited cell proliferation and viability of monolayers and spheroids of cancer cells adapted to various pHe conditions. Most importantly, combination of the two drugs had significantly larger inhibitory effects on PDAC cell survival. We propose that co-targeting H+/K+-ATPases and pH-sensitive K+ channels by re-purposing of pantoprazole and riluzole could provide novel acidosis-targeted therapies of PDAC.

Pantoprazole and riluzole target H+/K+-ATPases and pH-sensitive K+ channels in pancreatic cancer cells.

Pancreatic ductal adenocarcinoma (PDAC) remains the most lethal cancer type. PDAC is characterized by fibrotic, hypoxic, and presumably acidic tumor microenvironment (TME). Acidic TME is an important player in tumor development, progression, aggressiveness, and chemoresistance. The dysregulation of ductal ion transporters/channels might contribute to extracellular pH (pHe) acidification and PDAC progression. Our aim was to test whether H+/K+-ATPases and pH-sensitive K+ channels contribute to these processes and could be targeted by clinically approved drugs. We used human pancreatic cancer cells adapted to various pHe conditions and grown in monolayers and spheroids. First, we created cells expressing pHoran4 at the outer plasma membrane and showed that pantoprazole, the H+/K+-ATPase inhibitor, alkalinized pHe. Second, we used FluoVolt to monitor the membrane voltage (Vm) and showed that riluzole hyperpolarized Vm, most likely by opening of pH-sensitive K+ channels such as TREK-1. Third, we show that pantoprazole and riluzole inhibited cell proliferation and viability of monolayers and spheroids of cancer cells adapted to various pHe conditions. Most importantly, combination of the two drugs had significantly larger inhibitory effects on PDAC cell survival. We propose that co-targeting H+/K+-ATPases and pH-sensitive K+ channels by re-purposing of pantoprazole and riluzole could provide novel acidosis-targeted therapies of PDAC.

Unraveling Perspectives on Cancer: Exploring Individual Understandings and Implications

Cancer remains a formidable global health challenge, affecting millions of individuals annually through its complex and multifaceted manifestations. This paper delves into the intricate landscape of cancer biology, treatment modalities, and the crucial role of caregivers in the care continuum. Fundamentally, cancer arises from genetic mutations that disrupt the regulatory mechanisms governing cell division and growth. These mutations enable unchecked proliferation, leading to the formation of tumors categorized as benign or malignant. Malignant tumors, capable of metastasis, pose significant health risks as they spread from primary sites to distant tissues and organs. The etiology of cancer involves a confluence of genetic, environmental, and lifestyle factors. Genetic predisposition plays a pivotal role, with inherited mutations contributing to familial patterns of cancer. Environmental exposures, such as radiation and carcinogens, alongside lifestyle choices like tobacco use and dietary habits, further influence cancer development and progression. Advancements in cancer treatment encompass a spectrum of modalities tailored to cancer type, stage, and individual patient characteristics. These include chemotherapy, radiation therapy, surgery, targeted therapy, hormone therapy, and immunotherapy, each aiming to eradicate cancer cells, halt proliferation, or alleviate symptoms. Despite therapeutic innovations, cancer remains a significant public health concern with substantial global incidence and mortality rates. Integral to the cancer care ecosystem are caregivers who provide indispensable support to patients throughout their journey. Caregivers, whether family members, friends, or professionals, navigate diverse challenges inherent in caregiving, including emotional and physical demands. Understanding and addressing caregivers' needs and stressors are essential for optimizing patient outcomes and caregiver well-being. Research into cancer caregiving illuminates the complexities of this role, highlighting the importance of resilience, self-care strategies, and social support in mitigating caregiver stress. Tailored interventions and support services are crucial in enhancing caregivers' capacity to deliver effective care while maintaining their own health and resilience. Moreover, research underscores the broader societal impact of cancer, encompassing quality of life considerations, employment challenges, and psychosocial impacts on families and communities. Insights gleaned from these studies inform comprehensive support programs aimed at improving outcomes for patients and caregivers alike. In conclusion, this paper synthesizes current research to provide a comprehensive understanding of cancer's biological underpinnings, treatment modalities, and the critical role of caregivers. By integrating insights from diverse perspectives, it aims to inform strategies for cancer prevention, early detection, treatment optimization, and caregiver support. Ultimately, the goal is to mitigate the burden of cancer through collaborative efforts across scientific, medical, and caregiving domains. Cancer, a complex and multifaceted disease, presents significant challenges to both patients and caregivers worldwide. This investigation explores the pivotal role of caregivers in cancer treatment, emphasizing their influence, encountered difficulties, and self-care practices. Caregivers, whether familial or hired, are integral to patients' well-being, providing practical, emotional, and physical support throughout their journey. Despite their indispensable role, caregivers face numerous stressors, necessitating resilience and self-care strategies. Prioritizing self-care, seeking social support, and employing stress-relief techniques are essential for caregivers to manage stress effectively while ensuring the optimal care of their loved ones. By addressing caregiver stress, promoting their health and well-being, and utilizing available resources, caregivers can enhance their ability to provide compassionate care and navigate the complexities of cancer treatment. This abstract underscores the critical need for acknowledging and supporting caregivers, recognizing their invaluable contribution to the cancer care continuum.

Nanotechnology and Immunetherapy: reduction of hepatotoxicity and anti-antineoplastic efficiency

The integration of nanotechnology and immune therapy presents a revolutionary approach to cancer treatment, merging the precision of nanoscale engineering with the power of the immune system to combat malignancies. This review article explores the synergy between nanotechnology and immune therapy, highlighting its potential to enhance antineoplastic efficiency and mitigate hepatotoxicity, with a particular focus on liver cancer treatments. Nanotechnology offers novel solutions for targeted drug delivery, controlled release, and the co-delivery of therapeutic agents, thus improving the bioavailability and efficacy of immune therapies. By overcoming the challenges posed by the immunosuppressive tumor microenvironment (TME), nanotechnology-enabled strategies can potentiate the antitumor immune response and transform "cold" tumors into "hot" ones, making them more amenable to immune-mediated destruction. Despite promising advancements, the field faces challenges such as optimizing nanoparticle formulations for maximal therapeutic efficacy and safety, identifying suitable targeting ligands for specific cancer types, and addressing the heterogeneity of the TME. Comprehensive preclinical and clinical studies are required to assess the biodistribution, metabolism, and potential toxicity of nanocarriers. This review underscores the transformative potential of combining nanotechnology with immune therapy, offering insights into future directions for more effective, targeted, and safer cancer treatments.

Prediction of precancerous cervical cancer lesions among women living with HIV on antiretroviral therapy in Uganda: a comparison of supervised machine learning algorithms

BackgroundCervical cancer (CC) is among the most prevalent cancer types among women with the highest prevalence in low- and middle-income countries (LMICs). It is a curable disease if detected early. Machine learning (ML) techniques can aid in early detection and prediction thus reducing screening and treatment costs. This study focused on women living with HIV (WLHIV) in Uganda. Its aim was to identify the best predictors of CC and the supervised ML model that best predicts CC among WLHIV.MethodsSecondary data that included 3025 women from three health facilities in central Uganda was used. A multivariate binary logistic regression and recursive feature elimination with random forest (RFERF) were used to identify the best predictors. Five models; logistic regression (LR), random forest (RF), K-Nearest neighbor (KNN), support vector machine (SVM), and multi-layer perceptron (MLP) were applied to identify the out-performer. The confusion matrix and the area under the receiver operating characteristic curve (AUC/ROC) were used to evaluate the models.ResultsThe results revealed that duration on antiretroviral therapy (ART), WHO clinical stage, TPT status, Viral load status, and family planning were commonly selected by the two techniques and thus highly significant in CC prediction. The RF from the RFERF-selected features outperformed other models with the highest scores of 90% accuracy and 0.901 AUC.ConclusionEarly identification of CC and knowledge of the risk factors could help control the disease. The RF outperformed other models applied regardless of the selection technique used. Future research can be expanded to include ART-naïve women in predicting CC.

Nanotechnology and Immunetherapy: reduction of hepatotoxicity and anti-antineoplastic efficiency

The integration of nanotechnology and immune therapy presents a revolutionary approach to cancer treatment, merging the precision of nanoscale engineering with the power of the immune system to combat malignancies. This review article explores the synergy between nanotechnology and immune therapy, highlighting its potential to enhance antineoplastic efficiency and mitigate hepatotoxicity, with a particular focus on liver cancer treatments. Nanotechnology offers novel solutions for targeted drug delivery, controlled release, and the co-delivery of therapeutic agents, thus improving the bioavailability and efficacy of immune therapies. By overcoming the challenges posed by the immunosuppressive tumor microenvironment (TME), nanotechnology-enabled strategies can potentiate the antitumor immune response and transform "cold" tumors into "hot" ones, making them more amenable to immune-mediated destruction. Despite promising advancements, the field faces challenges such as optimizing nanoparticle formulations for maximal therapeutic efficacy and safety, identifying suitable targeting ligands for specific cancer types, and addressing the heterogeneity of the TME. Comprehensive preclinical and clinical studies are required to assess the biodistribution, metabolism, and potential toxicity of nanocarriers. This review underscores the transformative potential of combining nanotechnology with immune therapy, offering insights into future directions for more effective, targeted, and safer cancer treatments.

Single-cell resolution characterization of myeloid-derived cell states with implication in cancer outcome

Tumor-associated myeloid-derived cells (MDCs) significantly impact cancer prognosis and treatment responses due to their remarkable plasticity and tumorigenic behaviors. Here, we integrate single-cell RNA-sequencing data from different cancer types, identifying 29 MDC subpopulations within the tumor microenvironment. Our analysis reveals abnormally expanded MDC subpopulations across various tumors and distinguishes cell states that have often been grouped together, such as TREM2+ and FOLR2+ subpopulations. Using deconvolution approaches, we identify five subpopulations as independent prognostic markers, including states co-expressing TREM2 and PD-1, and FOLR2 and PDL-2. Additionally, TREM2 alone does not reliably predict cancer prognosis, as other TREM2+ macrophages show varied associations with prognosis depending on local cues. Validation in independent cohorts confirms that FOLR2-expressing macrophages correlate with poor clinical outcomes in ovarian and triple-negative breast cancers. This comprehensive MDC atlas offers valuable insights and a foundation for futher analyses, advancing strategies for treating solid cancers.

Next‐generation sequencing identifies that protein tyrosine phosphatase receptor type D mutation is favorable to immunotherapy in human cancer

AbstractProtein tyrosine phosphatase receptors (PTPRs) play a crucial part in numerous tumor processes. However, the effect of PTPR mutations on the immune checkpoint inhibitor (ICI) response needs to be further clarified. Next‐generation sequencing was performed on 453 cancer patients in our internal cohort. The genomic alterations, tumor mutation burden (TMB), neoantigens, and immune‐related features/pathways of other cohorts were analyzed. Here, protein tyrosine phosphatase receptor type D (PTPRD) has a high mutation frequency and an intensified co‐occurrence with other PTPRs. Patients who responded to ICI therapy were enriched with the PTPRD mutation (PTPRD‐MUT). PTPRD‐MUT patients had a higher objective response rate (44.1% vs. 29.1%), TMB/neoantigens, and longer overall survival time than PTPRD‐wild‐type (PTPRD‐WT) patients. Genomic alterations with a higher mutation frequency of genes (such as LRP1B) were enriched in PTPRD‐MUT patients. More abundant immune cells (including CD8+ T cells and macrophages) and upregulated immune‐related genes were found in PTPRD‐MUT patients. Moreover, Gene sets enrichment analyses showed that multiple antitumor immune pathways are activated in PTPRD‐MUT patients. Therefore, PTPRD‐MUT is beneficial for immunotherapy of multiple cancer types and may be a predictive biomarker of patient clinical outcomes.

Next‐generation sequencing identifies that protein tyrosine phosphatase receptor type D mutation is favorable to immunotherapy in human cancer

AbstractProtein tyrosine phosphatase receptors (PTPRs) play a crucial part in numerous tumor processes. However, the effect of PTPR mutations on the immune checkpoint inhibitor (ICI) response needs to be further clarified. Next‐generation sequencing was performed on 453 cancer patients in our internal cohort. The genomic alterations, tumor mutation burden (TMB), neoantigens, and immune‐related features/pathways of other cohorts were analyzed. Here, protein tyrosine phosphatase receptor type D (PTPRD) has a high mutation frequency and an intensified co‐occurrence with other PTPRs. Patients who responded to ICI therapy were enriched with the PTPRD mutation (PTPRD‐MUT). PTPRD‐MUT patients had a higher objective response rate (44.1% vs. 29.1%), TMB/neoantigens, and longer overall survival time than PTPRD‐wild‐type (PTPRD‐WT) patients. Genomic alterations with a higher mutation frequency of genes (such as LRP1B) were enriched in PTPRD‐MUT patients. More abundant immune cells (including CD8+ T cells and macrophages) and upregulated immune‐related genes were found in PTPRD‐MUT patients. Moreover, Gene sets enrichment analyses showed that multiple antitumor immune pathways are activated in PTPRD‐MUT patients. Therefore, PTPRD‐MUT is beneficial for immunotherapy of multiple cancer types and may be a predictive biomarker of patient clinical outcomes.

Prediction of moderate and severe toxicities of chemotherapy in older patients with cancer: a propensity weighted analysis of ELCAPA cohort.

Currently available predictive models for chemotherapy-related toxicity are not sufficiently discriminative in older patients with cancer and do not consider moderate toxicities. The purpose of this study was to identify factors associated with moderate and severe chemotherapy toxicities in older patients with cancer. Patients aged 70+ recruited in the prospective ELCAPA cohort were analyzed. A total of 837 patients with data on toxicities had received chemotherapy without other systemic treatment and were included between 2015 and 2022. To adjust for any imbalances in the distribution of covariates between patients receiving single-agent chemotherapy vs combination chemotherapy, we applied overlap weighting (a propensity-score-based technique). We used multinomial logistic regression. Median (interquartile range) age was 81 (77-84). Forty-one percent experienced moderate toxicity, and 33% experienced severe toxicity. Hematologic toxicities accounted for 53% of severe toxicities and 66% of moderate toxicities. Age <80 years, cancer type, metastatic status, Eastern Cooperative Oncology Group performance status (ECOG-PS) >1, no cognitive impairment were associated with combination chemotherapy decision. In a univariate analysis with overlap weighting, no factors were associated with moderate toxicity. Hemoglobin < 0g/dL and a CIRS-G score >12 were associated with severe toxicity. In a multivariate analysis, only hemoglobin < 10g/dL was independently associated with severe toxicity, adjusted OR 2.96 (95% CI, 1.20-7.29). By addressing indication bias for combination chemotherapy decision, only anemia and not cancer type, combination chemotherapy was predicting for severe chemotherapy-related toxicity in older patients with cancer. We did not find any predictors of moderate chemotherapy-related toxicity.

ADAR-Mediated A>I(G) RNA Editing in the Genotoxic Drug Response of Breast Cancer.

Epitranscriptomics is a field that delves into post-transcriptional changes. Among these modifications, the conversion of adenosine to inosine, traduced as guanosine (A>I(G)), is one of the known RNA-editing mechanisms, catalyzed by ADARs. This type of RNA editing is the most common type of editing in mammals and contributes to biological diversity. Disruption in the A>I(G) RNA-editing balance has been linked to diseases, including several types of cancer. Drug resistance in patients with cancer represents a significant public health concern, contributing to increased mortality rates resulting from therapy non-responsiveness and disease progression, representing the greatest challenge for researchers in this field. The A>I(G) RNA editing is involved in several mechanisms over the immunotherapy and genotoxic drug response and drug resistance. This review investigates the relationship between ADAR1 and specific A>I(G) RNA-edited sites, focusing particularly on breast cancer, and the impact of these sites on DNA damage repair and the immune response over anti-cancer therapy. We address the underlying mechanisms, bioinformatics, and in vitro strategies for the identification and validation of A>I(G) RNA-edited sites. We gathered databases related to A>I(G) RNA editing and cancer and discussed the potential clinical and research implications of understanding A>I(G) RNA-editing patterns. Understanding the intricate role of ADAR1-mediated A>I(G) RNA editing in breast cancer holds significant promise for the development of personalized treatment approaches tailored to individual patients' A>I(G) RNA-editing profiles.

ADAR-Mediated A&gt;I(G) RNA Editing in the Genotoxic Drug Response of Breast Cancer

Epitranscriptomics is a field that delves into post-transcriptional changes. Among these modifications, the conversion of adenosine to inosine, traduced as guanosine (A&gt;I(G)), is one of the known RNA-editing mechanisms, catalyzed by ADARs. This type of RNA editing is the most common type of editing in mammals and contributes to biological diversity. Disruption in the A&gt;I(G) RNA-editing balance has been linked to diseases, including several types of cancer. Drug resistance in patients with cancer represents a significant public health concern, contributing to increased mortality rates resulting from therapy non-responsiveness and disease progression, representing the greatest challenge for researchers in this field. The A&gt;I(G) RNA editing is involved in several mechanisms over the immunotherapy and genotoxic drug response and drug resistance. This review investigates the relationship between ADAR1 and specific A&gt;I(G) RNA-edited sites, focusing particularly on breast cancer, and the impact of these sites on DNA damage repair and the immune response over anti-cancer therapy. We address the underlying mechanisms, bioinformatics, and in vitro strategies for the identification and validation of A&gt;I(G) RNA-edited sites. We gathered databases related to A&gt;I(G) RNA editing and cancer and discussed the potential clinical and research implications of understanding A&gt;I(G) RNA-editing patterns. Understanding the intricate role of ADAR1-mediated A&gt;I(G) RNA editing in breast cancer holds significant promise for the development of personalized treatment approaches tailored to individual patients’ A&gt;I(G) RNA-editing profiles.

Secondary Analysis of Human Bulk RNA-Seq Dataset Suggests Potential Mechanisms for Letrozole Resistance in Estrogen-Positive (ER+) Breast Cancer

Estrogen receptor-positive (ER+) breast cancer is common among postmenopausal women and is frequently treated with Letrozole, which inhibits aromatase from synthesizing estrogen from androgens. Decreased estrogen slows the growth of tumors and can be an effective treatment. The increase in Letrozole resistance poses a unique problem for patients. To better understand the underlying molecular mechanism(s) of Letrozole resistance, we reanalyzed transcriptomic data by comparing individuals who responded to Letrozole therapy (responders) to those who were resistant to treatment (non-responders). We identified SOX11 and S100A9 as two significant differentially expressed genes (DEGs) between these patient cohorts, with “PLK1 signaling events” being the most significant signaling pathway. We also identified PRDX4 and E2F8 gene products as being the top mechanistic transcriptional markers for ER+ treatment resistance. Many of the significant DEGs that we identified play a known role in ER+ breast cancer or other types of cancer, which partially validate our results. Several of the gene products we identified are novel in the context of ER+ breast cancer. Many of the genes that we identified warrant further research to elucidate the more specific molecular mechanisms of Letrozole resistance in this patient population and could potentially be used as prognostic markers with further wet lab validation. We anticipate that these findings could contribute to improved detection and therapeutic outcomes in aromatase-resistant ER+ breast cancer patients.