Types Of Cancer Research Articles

Knockdown of PAIP1 Inhibits Breast Cancer Cell Proliferation by Regulating Cyclin E2 mRNA Stability.

Polyadenylate-binding protein-interacting protein 1 (PAIP1) is a protein that modulates translation initiation in eukaryotic cells. Studies have shown that PAIP1 was overexpressed in various type of cancers, and drives cancer progression by promoting cancer cell proliferation, invasion, and migration. In our previous study, we identified that PAIP1 was overexpressed in breast cancer, and the expression was correlated with poor prognosis. However, the biological function of PAIP1 in breast cancer has not been clearly understood. In this study, we constructed PAIP1 specifically silenced breast cancer cells. Then, cell proliferation, cell cycle distribution, and apoptosis were detected in PAIP1 knockdown cells. RNA-seq analysis was performed to predict the downstream target of PAIP1, and the molecular mechanism was explored. As a results, we found that knockdown of PAIP1 repressed cell proliferation, induced cell cycle arrest, and triggers apoptosis. Xenograft mouse model showed that knockdown of PAIP1 inhibits cell growth in vivo. RNA-seq predicted that CCNE2 mRNA was one of the downstream targets of PAIP1. In addition, we identified that knockdown of PAIP1-inhibited cell proliferation through modulating cyclin E2 expression. Mechanically, knockdown of PAIP1 reduces the expression of cyclin E2 by regulating the mRNA stability of cyclin E2. Moreover, in breast cancer tissues, we found that the expression of PAIP1 was positively correlated with cyclin E2. Taken together, our findings establish the role and mechanism of PAIP1 in breast cancer progression, indicating that PAIP1 would be a new therapeutic target for breast cancer treatment.

Metformin impacts the differentiation of mouse bone marrow cells into macrophages affecting tumour immunity

BackgroundEpidemiological studies suggest that metformin reduces the risk of developing several types of cancer, including gliomas, and improves the overall survival in cancer patients. Nevertheless, while the effect of metformin on cancer cells has been extensively studied, its impact on other components of the tumour microenvironment, such as macrophages, is less understood. ResultsMetformin-treated mouse bone marrow cells differentiate into spindle-shaped macrophages exhibiting increased phagocytic activity and tumour cell cytotoxicity coupled with modulated expression of co-stimulatory molecules displaying reduced sensitivity to inflammatory cues compared with untreated cells. Transcriptional analyses of metformin-treated mouse bone marrow-derived macrophages show decreased expression levels of pro-tumour genes, including Tgfbi and Il1β, related to enhanced mTOR/HIF1α signalling and metabolic rewiring towards glycolysis. SignificanceOur study provides novel insights into the immunomodulatory properties of metformin in macrophages and its potential application in preventing tumour onset and in cancer immunotherapy.

Cancer-associated SF3B1 Mutations Inhibit mRNA Nuclear Export by Disrupting SF3B1-THOC5 Interactions.

Mutations in SF3B1 are common in many types of cancer, which promotes cancer progression through aberrant RNA splicing. Recently, mRNA nuclear export has been reported to be defective in cells with SF3B1 K700E mutation. However, the mechanism remains unclear. Our study reveals that the K700E mutation in SF3B1 attenuates its interaction with THOC5, an essential component of mRNA nuclear export complex THO. Furthermore, SF3B1 mutation caused reduced binding of THOC5 with some mRNA and inhibited the nuclear export of these mRNA. Interestingly, THOC5 overexpression restores the nuclear export of these mRNA in cells with SF3B1 K700E mutation. Importantly, other types of cancer-associated SF3B1 mutations also inhibited mRNA nuclear export similarly, suggesting that it is common for cancer-associated SF3B1 mutation to inhibit mRNA nuclear export. Our research highlights the critical role of the THOC5-SF3B1 interaction in the regulation of mRNA nuclear export and provides valuable insights into the impact of SF3B1 mutations on mRNA nuclear export.

Ophthalmic Immune-Related Adverse Events and Association with Survival: Results from a Real-World Database

PurposeAssessing immune-related ocular toxicities from immune checkpoint inhibitors (ICIs) is crucial, though rare. This study, utilizing real-world data, examines the occurrence of ophthalmic immune-related adverse events (irAEs) after ICI treatment and their impact on overall survival. DesignA retrospective cohort study MethodsData were obtained from TriNetX, an aggregated electronic health records database. Patients who developed ophthalmic irAEs within 1 year after the first instance of ICI therapy were included. Participants with defined ocular toxicities 6 months before ICI treatment were excluded. Subjects were paired with controls using propensity scores derived from demographics and cancer type. A Cox proportional hazard model was used to determine hazard ratios. A Kaplan-Meier survival function was evaluated with the log-rank test based on the development of ophthalmic irAEs in a 12-month landmark analysis. ResultsA cohort of 41,020 patients comprising 57.4% males with a mean age of 65.2±11.9 years was included. The five most prevalent ophthalmic irAEs in this cohort were dry eye syndrome (2%), conjunctivitis (0.87%), blepharitis (0.51%), anterior uveitis (0.39%), and keratitis (0.38%). Dry eye syndrome was the most common irAE among all ICI classes. Subjects taking CTLA-4 inhibitor plus PD-1 inhibitor and CTLA-4 inhibitors had higher rates of anterior uveitis (1.39% and 1.29%, respectively) than PD-1 inhibitors (0.27%) and PD-L1 inhibitors (0.14%) within 1 year after taking ICI. After a 12-month landmark analysis, there was a significant decreased chance of survival for the following categories: any ophthalmic irAE (HR, 1.37; 95% CI, 1.20-1.56; P < 0.0001), neuro-ophthalmic irAE (HR, 1.53; 95% CI, 1.09-2.14; P = 0.0124), and cornea and ocular surface irAE (HR, 1.34; 95% CI, 1.15-1.56; P < 0.0001). ConclusionsOphthalmic irAEs involving the anterior segment are more frequent than the posterior segment, regardless of ICI class. Ophthalmic irAEs may also portend decreased survival. This insight could help guide clinicians aggressively manage irAEs and allow patients to continue ICI therapy despite having ocular issues.

The role of stereotactic body radiotherapy in oligoprogressive malignant disease (RADIANT): oncologic outcomes from a phase 2 non-randomized controlled trial

BackgroundIn oligoprogressive (OP) cancer there are a limited numbers of metastatic areas progressing on a background of stable or responding widespread cancer. While the standard-of-care for OP is changing systemic therapy (ST), stereotactic body radiotherapy (SBRT) is being explored as an alternative local therapy targeting the sites of progression. Materials/methodsXXX (NCTXXX) was a single-centre phase-2 study of patients with metastatic genitourinary (GU), breast and gastrointestinal (GI) cancers, receiving ST for >3 months, with radiographic OP disease in <5 sites. Patients received SBRT to all OP disease in 1-5 fractions, and were maintained on ST. The primary endpoint was the cumulative incidence of change in ST estimated using Aalen-Johansen method. Secondary endpoints included progression-free survival (PFS) and overall survival (OS) estimated using Kaplan-Meier method, toxicity, and health-related quality-of-life (HRQOL). Comparisons between diagnosis groups were done using log-rank test. A two-sided p-value of <0.05 was considered as statistical significance. ResultsSeventy patients were analyzed, with median age 69 years; 32 patients (46%) were female; median number of lines of prior ST was 3. Primary sites were GU (n=32; 46%), breast (n=23; 33%) and GI (n=15; 21%). Median follow-up was 12.3 months (IQR 8.2-21.6). At 1-year, change in ST occurred in 47% (95% CI 36-61%) (GU 45%, breast 41%, GI 60%, p=0.23). PFS at 1-year was 32% (95% CI 23-45%), and median PFS was 4.7 months (95% CI 3.8-8.1) (GU 4.8, breast 6.5, GI 3.2), which significantly differed by disease type (p=0.006). OS was 75% at 1-year (95% CI 65-87%), which significantly differed between cancer type (GU 86%, breast 96%, GI 22%, p<0.001). Cumulative incidence of late grade >2 toxicity was 1.2%, with 1 patient experiencing late grade 3 toxicity, and no grade 4-5 acute or late toxicities. HRQOL declined from mean (standard deviation) of 66.9 (20.2) at baseline to 60.5 (22.2) at 6 months, which did not meet the threshold for a minimal clinically important difference. ConclusionsSBRT for OP metastases delayed change in ST in approximately half of patients, warranting investigation in randomized trials.

Prospective multicenter study using artificial intelligence to improve dermoscopic melanoma diagnosis in patient care

BackgroundEarly detection of melanoma, a potentially lethal type of skin cancer with high prevalence worldwide, improves patient prognosis. In retrospective studies, artificial intelligence (AI) has proven to be helpful for enhancing melanoma detection. However, there are few prospective studies confirming these promising results. Existing studies are limited by low sample sizes, too homogenous datasets, or lack of inclusion of rare melanoma subtypes, preventing a fair and thorough evaluation of AI and its generalizability, a crucial aspect for its application in the clinical setting.MethodsTherefore, we assessed “All Data are Ext” (ADAE), an established open-source ensemble algorithm for detecting melanomas, by comparing its diagnostic accuracy to that of dermatologists on a prospectively collected, external, heterogeneous test set comprising eight distinct hospitals, four different camera setups, rare melanoma subtypes, and special anatomical sites. We advanced the algorithm with real test-time augmentation (R-TTA, i.e., providing real photographs of lesions taken from multiple angles and averaging the predictions), and evaluated its generalization capabilities.ResultsOverall, the AI shows higher balanced accuracy than dermatologists (0.798, 95% confidence interval (CI) 0.779–0.814 vs. 0.781, 95% CI 0.760–0.802; p = 4.0e−145), obtaining a higher sensitivity (0.921, 95% CI 0.900–0.942 vs. 0.734, 95% CI 0.701–0.770; p = 3.3e−165) at the cost of a lower specificity (0.673, 95% CI 0.641–0.702 vs. 0.828, 95% CI 0.804–0.852; p = 3.3e−165).ConclusionAs the algorithm exhibits a significant performance advantage on our heterogeneous dataset exclusively comprising melanoma-suspicious lesions, AI may offer the potential to support dermatologists, particularly in diagnosing challenging cases.

Androgen receptor expression and clinical characteristics in breast cancer

ObjectiveTo investigate the relationship between the expression of androgen receptor (AR) and clinical characteristics in breast cancer.Patients and methodsThe clinical records of all 432 patients tested for AR in our institution between January 2020 and May 2023 were reviewed. Clinical characteristics, age, menopausal status, tumor node metastasis (TNM) stage, distant metastasis, pathological complete response (pCR), histopathological features histological grade, estrogen receptor (ER), progesterone receptor, Her-2, Ki-67, and molecular subtype were registered for all patients.ResultsAbout 377 (87.27%) of the 432 patients had AR expression.No significant difference in AR expression was found with age, menopausal status, TNM stage of primary tumor, or pCR. AR was positively and significantly associated with the histological grade, and recurrence. The AR expression was significantly related with molecular subtypes, including ER, PR Her-2, Ki67 and molecular subtype. ER (OR = 10.489, 95%CI: 5.470–21.569), PR (OR = 7.690, 95%CI: 3.974–16.129, Her-2 (OR = 10.489, 95%CI: 2.779–23.490 and tumor recurrence (OR = 0.110, 95%CI: 0.031–0.377 were significant independent risk factors affecting AR expression.ConclusionsAR expression can serve as a reliable basis for judging the clinical molecular types and poor prognosis for breast cancer. AR may be a novel biomarker and target in AR-positive breast cancer depending on significant difference in AR expression among different molecular types of breast cancer.

A Comparative Analysis of Computational Strategies in Multi-Epitope Vaccine Design Against Human Papillomavirus and Cervical Cancer.

Given the critical role of human papillomavirus (HPV) in the cause of cervical cancer and other malignancies, there is a need for innovative approaches to preventing this infection. It has been shown that immunoinformatics is an important strategy in computational vaccinology. It is used to design new multi-epitope vaccines against different types of HPV and subsequent cervical cancer. This paper reviews the scope of the entire computational pipeline of HPV vaccine design, starting from data analysis at the genomic and proteomic levels and continuing to epitope predictions of the innate and adaptive immune systems. The search strategy was based on investigating original articles published in "Google Scholar" and "PubMed" from 2015 to 2023-2024. The terms "Immunoinformatics", "Bioinformatics", "Human papillomavirus (HPV)", "Vaccine design", "In silico vaccine design", "Multi-epitope vaccine design", "Vaccinology" and "HPV vaccine" were used to for this purpose. We discussed various essential tools involved in the computational design of the vaccine process, e.g., sequence analysis, epitope prediction, conservancy analysis, tertiary structure modeling, refinement, molecular docking, molecular dynamics (MD) simulation, and in silico cloning. This review article describes immunoinformatics methods that facilitate the design of a multi-epitope vaccine against HPV. However, this pipeline can also be used to design novel chimeric vaccines for other pathogens.

Transcription factor Yin Yang 1 enhances epithelial-mesenchymal transition, migration, and stemness of non-small cell lung cancer cells by targeting sonic hedgehog.

Non-small cell lung cancer (NSCLC) is a frequent type of lung cancer. Transcription factor Yin Yang 1 (YY1), an endogenous transcription factor containing zinc finger structure, can accelerate NSCLC progression. However, the impact of YY1 on the stemness of NSCLC cells and the mechanism of promoting NSCLC cell progression is unclear. YY1 and Sonic hedgehog (Shh) expressions were monitored by RT-qPCR, western blot, and immunohistochemistry. Overall survival was tested through Kaplan-Meier analysis. The interaction between YY1 and Shh was confirmed. Then, cell migration, stemness, and epithelial-mesenchymal transition (EMT) were assessed with functional experiments in vitro and in vivo. YY1 and Shh were highly expressed in NSCLC tissues and positively correlated with the poor OS of NSCLC patients. Functional experiments denoted that YY1 or Shh overexpression could accelerate EMT, migration, and stemness of NSCLC cells, and YY1 or Shh knockdown played the opposite role to its overexpression. Mechanism analysis disclosed that Shh, as a target gene of YY1, was positively related to YY1. The rescued experiment manifested that Shh silencing could reverse the induction effect of YY1 overexpression on EMT, migration, and stemness of NSCLC cells. In vivo experiments also confirmed that YY1 could accelerate tumor growth and EMT and weaken apoptosis. YY1 promotes NSCLC EMT, migration, and stemness by Shh, which might be novel diagnostic markers and therapeutic targets for NSCLC therapy.

Potential Advantages of Idarubicin-Loaded Trastuzumab-Coated Liposomes for Combating Head and Neck Squamous Cancer Cells.

Head and neck squamous cell carcinoma (HNSCC) with a high mortality rate is among the most common types of cancer in the world. Human epidermal growth factor receptor 2 (HER2) is expressed higher than normal level in the most HNSCC tumors, making them resistant to chemotherapy and radiotherapy. Therefore, HER2 has been introduced as a suitable target for anticancer drugs. The aim of this study is to examine the efficacy of a treatment protocol involving targeted delivery of idarubicin encapsulated in trastuzumab-decorated liposomes to HNSCC cells. In the current experimental study, efficacies of idarubicin, prepared liposomal idarubicin, and constructed immunoliposomal idarubicin (trastuzumab-decorated) were investigated in killing HN5 cells, a HER2- overexpressing HNSCC-originating cell line. Liposomal content of idarubicin and trastuzumab were qualified by UVVisible spectroscopy and preparations were characterized for shape and size by atomic force microscopy (AFM) and dynamic light scattering (DLS). To clarify role of the missing parts of the available crystal structure (PDB ID: 1n8z) within trastuzumab-HER2 interactions, we used a 40 ns molecular dynamic simulation approach. Based on the obtained results, liposomal idarubicin showed higher toxicity of the encapsulated drug on HN5 cells compared to the traditional free drug formulations. The immunoliposomal form of idarubicin was more effective than the liposomal formulation, in killing of HN5 cells. In addition, simulation of interactions between trastuzumab and HER2 revealed that the missing parts (in the crystal structure) of HER2 have critical interaction with trastuzumab, through salt-bridges and hydrogen bonds. It seems that the prepared immunoliposomes could attach more efficiently to HER2 overexpressing cells, which consequently leads to increasing cellular uptake of idarubicin through a receptor-mediated endocytosis mechanism. Moreover, simulation of the interaction between HER2 and trastuzumab suggested considerable possibilities for increasing trastuzumab affinity to HER2.

An observational and genetic investigation into the association between psoriasis and risk of malignancy

The relationship between psoriasis and site-specific cancers remains unclear. Here, we aim to investigate whether psoriasis is causally associated with site-specific cancers. We use observational and genetic data from the UK Biobank, obtaining GWAS summary data, eQTL analysis data, TCGA data, and GTEx data from public datasets. We perform PheWAS, polygenic risk score analysis, and one-sample and two-sample Mendelian randomization analyses to investigate the potential causal associations between psoriasis and cancers. In the unselected PheWAS analysis, psoriasis is associated with higher risks of 16 types of cancer. Using one-sample Mendelian randomization analyses, it is found that genetically predicted psoriasis is associated with higher risks of anal canal cancer, breast cancer, follicular non-Hodgkin’s lymphoma and nonmelanoma skin cancer in women; and lung cancer and kidney cancer in men. Our two-sample Mendelian randomization analysis indicates that psoriasis is causally associated with breast cancer and lung cancer. Gene annotation shows that psoriasis-related genes, such as ERAP1, are significantly different in lung and breast cancer tissues. Taken together, clinical attention to lung cancer and breast cancer may be warranted among patients with psoriasis.

Prognostic Significance of the Advanced Lung Cancer Inflammation Index in Metastatic Small Cell Lung Cancer: A Retrospective Analysis of 96 Patients.

BACKGROUND The advanced lung cancer inflammation index (ALI) is regarded as a potential indicator of systemic inflammation. This retrospective study aimed to evaluate the prognostic role of the ALI in 96 patients with advanced small cell lung cancer (SCLC). MATERIAL AND METHODS This retrospective study included 96 patients who were diagnosed with extensive stage SCLC in a single institution between 2016 and 2022. The formula for ALI is body mass index (kg/m²)×serum albumin (g/dL)/neutrophil to lymphocyte ratio. Patients were divided into low inflammation (ALI ≥32.5) and high inflammation (ALI <32.5) groups. Kaplan-Meier analysis and Cox proportional analysis were conducted to assess the association between the ALI and patient prognosis. RESULTS Median age was 61 (range: 41-82) years. Median follow-up was 9 months, and median overall survival (OS) was 10 months (95% CI: 7.75-12.45). A lower ALI score (ALI <32.5) was correlated with a poorer OS than was a higher ALI score (median OS 7 months for ALI <32.5 95% CI: 4.6-9.3 vs 15 months for ALI ≥32.5, 95% CI: 10.6-19.3, P<0.001). In the multivariate analysis, ALI score, Eastern Cooperative Oncology Group performance status, brain metastasis, and bone metastasis were identified as independent prognostic factors. CONCLUSIONS ALI score is a substantial predictor of survival in SCLC as in other types of cancer types. Patients with a low ALI score have poorer survival. Assessment of ALI can identify lung cancer patients at high risk of poor prognosis and can be a useful prognostic marker in clinical practice.

A comprehensive review of tubule formation in histopathology images: advancement in tubule and tumor detection techniques

Breast cancer, the earliest documented cancer in history, stands as a foremost cause of mortality, accounting for 684,996 deaths globally in 2020 (15.5% of all female cancer cases). Irrespective of socioeconomic factors, geographic locations, race, or ethnicity, breast cancer ranks as the most frequently diagnosed cancer in women. The standard grading for breast cancer utilizes the Nottingham Histopathology Grading (NHG) system, which considers three crucial features: mitotic counts, nuclear pleomorphism, and tubule formation. Comprehensive reviews on features, for example, mitotic count and nuclear pleomorphism have been available thus far. Nevertheless, a thorough investigation specifically focusing on tubule formation aligned with the NHG system is currently lacking. Motivated by this gap, the present study aims to unravel tubule formation in histopathology images via a comprehensive review of detection approaches involving tubule and tumor features. Without temporal constraints, a structured methodology is established in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, resulting in 12 articles for tubule detection and 67 included articles for tumor detection. Despite the primary focus on breast cancer, the structured search string extends beyond this domain to encompass any cancer type utilizing histopathology images as input, focusing on tubule and tumor detection. This broadened scope is essential. Insights from approaches in tubule and tumor detection for various cancers can be assimilated, integrated, and contributed to an enhanced understanding of tubule formation in breast histopathology images. This study compiles evidence-based analyses into a cohesive document, offering comprehensive information to a diverse audience, including newcomers, experienced researchers, and stakeholders interested in the subject matter.

Neurological hospitalisations in childhood cancer survivors treated before 2001: findings from the French Childhood Cancer Survivor Study cohort

PurposeChildhood cancer survivors (CCS) have an increased risk of developing late chronic diseases, which can be influenced by the cancer type and its treatment. These chronic diseases can be severe and disabling, typically emerging years to decades after treatment. These deficits negatively impact quality of life, intelligence quotient, and memory. This study investigated how much the cancer type and treatment could affect the neurological hospitalisations in the French Childhood Cancer Survivors Study (FCCSS).MethodsWe included 5579 childhood cancer survivors (CCS), diagnosed with solid tumours or lymphoma between 1945 and 2000, treated before 2001 and below the age of 21 years at initial treatment. The follow-up period was from 2006 to 2018. Hospitalisation data were obtained by linkage with the National Health Data System. We calculated the relative hospitalisation rate (RHRs) and absolute excess rate (AERs). Multivariable analyses were conducted using a Generalized Linear Model (GLM) with a Poisson distribution to estimate the association between neurological hospitalisation and patient characteristics. The expected number of hospitalisations served as an offset to compare the risk for FCCSS survivors with that of the reference population. Risk estimates were reported as relative risk (RR) with 95% confidence intervals.ResultsThe hospitalisation rate for CCS was 114.2 per 10,000 person-years (PY), compared to 48.4 in the reference population. The highest hospitalisation rates were observed for epilepsy (AER = 27.1 per 10000 PY, 95%CI: 23.5–31.2 and RHR = 5.1, 95%CI 4.4–5.7). In multivariable analyses, central nervous system (CNS) tumours survivors had the highest relative risk (RR) of hospitalisation (RR = 9.4, 95%CI: 6.7–13.1) followed by neuroblastoma survivors (RR = 2.5, 95%CI: 1.7–3.7). In the whole population, survivors who received radiation to the head and neck had a significantly higher risk of hospitalisation (RR = 3.9, 95%CI: 3.3–4.7) compared to those who did not receive radiotherapy.ConclusionsHead and neck irradiation was identified as a strong risk factor for hospitalisation. This underlines the importance of implementing specific neurologic surveillance programs for at-risk individuals.

Impact of the COVID-19 pandemic on cancer mortality in Brazil

BackgroundIn the first year of the COVID-19 pandemic, data projections indicated an increase in cancer mortality for the following years due to the overload of health services and the replacement of health priorities. The first studies published with data from mortality records have not confirmed these projections. However, cancer mortality is not an outcome that occurs immediately, and analyses with more extended follow-up periods are necessary. This study aims to analyze the impact of the COVID-19 pandemic on the mortality from all types and the five most common types of cancer in Brazil and investigate the relationship between the density of hospital beds and mortality from COVID-19 in cancer patients in Brazil’s Intermediate Geographic Regions (RGIs).MethodsThe Brazilian Mortality Information System provided data on the deaths from trachea, bronchus, and lung, colorectal, stomach, female breast, and prostate cancer and all types of cancer, and from COVID-19 in individuals who had cancer as a contributing cause of death. Predicted rates for 2020–2022 were compared with the observed ones, through a rate ratio (RR). An association analysis, through multivariate linear regression, was carried out between mortality from COVID-19 in cancer patients, the rate of hospital beds per 100,000 inhabitants, and the Human Development Index of the 133 RGIs of Brazil.ResultsIn 2020, 2021, and 2022, mortality from all cancers in Brazil was lower than expected, with an RR of 0.95, 0.94, and 0.95, respectively, between the observed and predicted rates. Stomach cancer showed the largest difference between observed and expected rates: RR = 0.89 in 2020 and 2021; RR = 0.88 in 2022. Mortality from COVID-19 in cancer patients, which reached its peak in 2021 (6.0/100,000), was negatively associated with the density of hospital beds in the public health system.ConclusionsThe lower-than-expected cancer mortality during 2020–2022 seems to be partly explained by mortality from COVID-19 in cancer patients, which was probably underestimated in Brazil. The findings suggested a protective role of the availability of hospital care concerning deaths due to COVID-19 in this population. More extensive follow-up is needed to understand the impact of the COVID-19 pandemic on cancer mortality.

Validated Administrative Data-Based ICD-10 Algorithms for Chronic Conditions

ObjectiveThis systematic review aimed to identify ICD-10 based validated algorithms for chronic conditions using health administrative data. MethodsA comprehensive systematic literature search using Ovid MEDLINE, Embase, PsycINFO, Web of Science and CINAHL was performed to identify studies, published between 1983 and May 2023, on validated algorithms for chronic conditions using administrative health data. Two reviewers independently screened titles and abstracts and reviewed full text of selected studies to complete data extraction. A third reviewer resolved conflicts arising at the screening or study selection stages. The primary outcome was validated studies of ICD-10 based algorithms with both sensitivity and PPV of ≥70%. Studies with either sensitivity or PPV &lt;70% were included as secondary outcomes. ResultsOverall, the search identified 1686 studies of which 55 met the inclusion criteria. Combining a previously published literature search, a total of 61 studies were included for data extraction. Of these, 30 studies demonstrated algorithms with high validity and 30 showed moderate validity. Studies with highly valid algorithms were based on administrative data from different countries including Canada, USA, Australia, Japan, France, South Korea, and Taiwan. Validated algorithms with PPV and sensitivity of ≥70% were identified for more than 40 chronic conditions that included several types of cancers, cardiovascular conditions, kidney diseases, gastrointestinal disorders, and peripheral vascular diseases, amongst others. ConclusionWith ICD-10 prominently used across the world, this up-to-date systematic review can prove to be a helpful resource for research and surveillance initiatives using administrative health data for identifying chronic conditions.

The (dis)continuing of antithrombotic drugs and its implications for occurrence of adverse cardiovascular and bleeding events in cancer patients during end of life

Background and ObjectivesFor patients receiving end-of-life care, adjusting polypharmacy and deprescription of potentially harmful medicines are important impactors on quality-of-life. Antithrombotic therapies (ATT) are used by 30-50% of patients with cancer, rising to 80% in older cancer patients, and are often continued until a quality-of-life-impacting bleeding event, or a patient is physically unable to take oral medication. We aimed to describe the use of ATT and occurrence of clinical outcomes in patients with cancer during end-of-life care. ApproachLinked health and administrative data in SAIL were used to identify end-of-life cancer patients diagnosed in Wales, focusing on cancer types with an estimated 1-year survival time. Survival analysis was used to describe current ATT usage and to investigate the associations between ATT usage and major cardiovascular and bleeding events. Results21,880 individuals were diagnosed with the pre-defined cancer types between January 2013 and December 2019, 5,660 (26%) of these were taking ATT at diagnosis. During the study period 1670 (30%) were discontinued. Median survival time of patients taking ATT at diagnosis was 169 (IQR 158-180) days, while median time to deprescription was 206 (IQR 190-224) days. Among ATT-users diagnosis, 460 (8%) and 900 (16%) experienced a major bleed or a cardiovascular event, respectively, within 1 year following diagnosis, compared to 1100 (7%) and 1930 (12%) among those who were not prescribed ATT at diagnosis. Conclusions and ImplicationsOur research highlights the need for careful assessment and management of ATT in the interest of improving quality-of-life for patients with cancer during end-of-life care.

The tumor microenvironment in therapy resistance

Chemotherapy alone or in conjunction with surgery and radiation is often used to treat various cancer types. While effective at treating some tumors, the response varies across patients with different malignancies. For some cancers, such as glioblastoma, ovarian cancer, and soft tissue sarcoma, 85%–100% of patients experience cancer recurrence and develop chemotherapy resistance, which often leads to worse prognoses. These alarming statistics highlight an urgent need to better understand the landscape of therapy resistance in cancer, in order to develop improved treatment strategies and prevent recurrence. A central focus has been the investigation of resistant tumor subclones and whether the use of different alkylating agents and/or immune checkpoint inhibitors can ablate different clones. However, very little effort has been directed towards studies of the tumor microenvironment, a complex ecosystem of blood vessels, fibroblasts, immune cells, signaling molecules, and extracellular matrix, in the context of therapy resistance. In this perspective, we provide an overview of different platforms, tools, and techniques that have been developed and used to identify tumor microenvironment alterations due to therapy resistance. We also address potential therapeutic strategies that involve components of the tumor milieu and have been identified and tested to overcome treatment-induced resistance. Identifying microenvironmental changes post-resistance presents opportunities for new targeted treatment strategies. The current state of the literature suggests a dire need for more engineered models that probe specific microenvironment contributors to therapy resistance or ways in which the tumor tissue can be harnessed to mitigate resistance.

Pan-cancer analysis reveals CCL5/CSF2 as potential predictive biomarkers for immune checkpoint inhibitors

BackgroundCurrently, there are no optimal biomarkers available for distinguishing patients who will respond to immune checkpoint inhibitors (ICIs) therapies. Consequently, the exploration of novel biomarkers that can predict responsiveness to ICIs is crucial in the field of immunotherapy.MethodsWe estimated the proportions of 22 immune cell components in 10 cancer types (6,128 tumors) using the CIBERSORT algorithm, and further classified patients based on their tumor immune cell proportions in a pan-cancer setting using k-means clustering. Differentially expressed immune genes between the patient subgroups were identified, and potential predictive biomarkers for ICIs were explored. Finally, the predictive value of the identified biomarkers was verified in patients with urothelial carcinoma (UC) and esophageal squamous cell carcinoma (ESCC) who received ICIs.ResultsOur study identified two subgroups of patients with distinct immune infiltrating phenotypes and differing clinical outcomes. The patient subgroup with improved outcomes displayed tumors enriched with genes related to immune response regulation and pathway activation. Furthermore, CCL5 and CSF2 were identified as immune-related hub-genes and were found to be prognostic in a pan-cancer setting. Importantly, UC and ESCC patients with high expression of CCL5 and low expression of CSF2 responded better to ICIs.ConclusionWe demonstrated CCL5 and CSF2 as potential novel biomarkers for predicting the response to ICIs in patients with UC and ESCC. The predictive value of these biomarkers in other cancer types warrants further evaluation in future studies.

Downregulation of RhoB Inhibits Cervical Cancer Progression and Enhances Cisplatin Sensitivity

RhoB, a member of the Rho GTPase family, has been implicated in the malignant progression of various cancer types. However, its role in cervical cancer (CC) remains unclear. Therefore, this study aims to elucidate the biological function of RhoB in CC and its relationship with cisplatin sensitivity. We analyzed data from the TCGA, GTEx, and GEO databases, revealing that RhoB mRNA expression is downregulated in CC tissues compared to normal cervical tissues. The further analysis of the TCGA database and Tongji samples showed that CC patients with a high RhoB expression had a shorter overall survival (OS). Subsequently, we found that the knockdown of RhoB inhibited the proliferation, migration, and invasion of cancer cells, while increasing apoptosis. Through Western blot (WB) analysis, we found that knocking down RhoB resulted in an increased expression of the epithelial marker E-cadherin, while the levels of N-cadherin, MMP2, MMP9, Vimentin, and Snail1 were reduced. Additionally, RhoB mRNA expression was upregulated in CC tissues after chemotherapy compared to CC tissues before chemotherapy. In CC cells, RhoB expression increased with cisplatin concentration, and the IC50 value decreased following RhoB knockdown. Moreover, the knockdown of RhoB could enhance the cellular apoptosis triggered by cisplatin. This study demonstrated that RhoB plays an oncogenic role in CC and that its knockdown could enhance the sensitivity of CC cells to cisplatin.