To analyze the impact of global population aging on cancer epidemiology, with a focus on the incidence and mortality rates among individuals aged 60 years and above. We utilized open-source data, retrieving population age estimates from the United Nations Population Division website. The GLOBOCAN 2020 database provided estimates for cancer cases and deaths in 2020 and 2040, while the Global Burden of Disease 2019 database supplied estimates of new cancer cases worldwide from 2000 to 2019. Inclusion criteria considered individuals aged 60 years and over, focusing on the top five deadliest cancers. The cohort-component method was employed for population prediction, with age-specific incidence and mortality rates estimated for 2020 used to forecast the cancer burden. In 2021, the global population aged over 60 years accounted for 13.7%, with Europe/North America and Australia/New Zealand having the highest proportions. The older population is predicted to reach 19.2% by 2040. In 2020, of the 19.3 million new cancer cases worldwide, 64% occurred in individuals aged 60 and above, contributing to 71.3% of cancer-related deaths. The five most common cancer sites were the lung, colorectum, prostate, breast, and stomach. Cancer incidence and deaths are projected to rise significantly among older individuals, reaching 20.7 million new cases and 12.7 million deaths by 2040. Older age, tobacco use, dietary factors, alcohol consumption, and high body mass index (BMI) were identified as major risk factors for various cancers in this demographic. This study reveals a significant rise in cancer incidence and mortality among the elderly due to global population aging. The urgency for targeted interventions in cancer prevention, screening, and treatment for older individuals is emphasized. Despite acknowledged limitations, these findings contribute valuable insights to inform strategies for managing cancer in the elderly amidst evolving demographic trends.

Purpose: We used targeted capture sequencing to analyze TP53‐mutated circulating tumor DNA (ctDNA) in metastatic breast cancer patients and to determine whether TP53 mutation has predictive value for anti‐human epidermal growth factor receptor 2 (HER2) treatment for in HER2 amplification‐positive patients (HER2+) and HER2 mutation‐positive, amplification‐negative (HER2−/mut) patients.Patients and Methods: TP53 mutation features were analyzed in the Geneplus cohort (n = 1184). The MSK‐BREAST cohort was used to explore the value of TP53 mutation in predicting anti‐HER‐2 antibody efficacy. Sequencing of ctDNA in phase Ib, phase Ic, phase II clinical trials of pyrotinib (HER2+ patients), and an investigator‐initiated phase II study of pyrotinib (HER2−/mut patients) were performed to analyze the relationships between TP53 mutation and prognosis for HER2 TKIs. The MSK‐BREAST cohort, MutHER, and SUMMIT cohort were used for verification.Results: TP53 mutations were detected in 53.1% (629/1184) of patients in the Geneplus cohort. The TP53 mutation rate was higher in HR‐negative (p < 0.001) and HER2 amplification‐positive (p = 0.015) patients. Among patients receiving anti‐HER2 antibody therapy, those whose tumors carried TP53 mutations had a shorter PFS (p = 0.004). However, the value of TP53 mutation in predicting HER2 TKI response was inconsistent. In HER2+ patients, no difference in PFS was observed among patients with different TP53 statuses in the combined analysis of the pyrotinib phase Ib, phase Ic, and phase II clinical trials (p = 1.00) or in the MSK‐BREAST cohort (p = 0.62). In HER2−/mut patients, TP53 mutation‐positive patients exhibited a trend toward worse prognosis with anti‐HER2 TKI treatment than TP53‐wild‐type patients in our investigator‐initiated phase II study (p = 0.15), and this trend was confirmed in the combined analysis of the MutHER and SUMMIT cohorts (p = 0.01).Conclusions: TP53 mutation can be used to identify biomarkers of anti‐HER2 antibody drug resistance in HER2+ patients and HER2 TKI resistance in HER2−/mut patients.

Everolimus, an inhibitor of mammalian target of rapamycin (mTOR), has been shown to increase the efficacy of endocrine therapies in hormone receptor (HR)-positive metastatic breast cancer. However, because breast cancer is a highly heterogeneous disease, the responses of different patients to everolimus may vary. Therefore, we performed this study to better select patients who will benefit most from or be resistant to everolimus. Patients with HR-positive breast cancer who were treated with everolimus at the Cancer Hospital, Chinese Academy of Medical Sciences from February 2014 to March 2017 were enrolled in the present study. Mutations in ctDNA were assayed in 1021 tumor-related genes via gene panel target capture-based next-generation sequencing. In total, 120 patients with metastatic breast cancer who were treated with everolimus were enrolled in the present study. The median progression-free survival (PFS) of all patients was 5.1 months (95% confidence interval [CI] 3.9–6.3 months). No difference in survival was observed between patients who received endocrine drugs used in previous treatment regimens and patients who did not receive these drugs (median PFS 5.2 and 5.1 months, respectively, p > 0.05). Additionally, we did not find any difference in outcomes between patients who had primary resistance to previously used endocrine drugs and patients who had nonprimary resistance to previous treatments (p > 0.05). Multivariate analysis showed that < 3 metastatic sites, < 2 lines of previous endocrine therapy, < 2 lines of previous chemotherapy, and treatment with everolimus combined with fulvestrant were associated with improved survival (p < 0.05). Sixteen patients underwent ctDNA analysis before everolimus treatment. The frequency of PIK3CA gene mutations was 62.5%, and H1047R was the most frequently detected mutation. Patients with the PIK3CA/H1047R mutation had longer PFS than patients with wild-type or other mutant forms of PIK3CA, and the median PFS in these two groups of patients was 8.8 and 4.1 months, respectively (p < 0.05). Our data suggest that patients who receive more lines of chemotherapy or endocrine therapy are less likely to benefit from everolimus. For everolimus combination therapy, we can even select endocrine drugs that gave rise to primary resistance in previous treatments. Additionally, the PIK3CA/H1047R mutation may be a potential biomarker of sensitivity to everolimus.

The current state of oncology medical services is not encouraging and is unable to fully meet the needs of patients with cancer. In recent years, rapidly developing artificial intelligence technology and gradual advancements in mobile phones, sensors, and wearable devices, which have made these more compact, affordable, and popular, have greatly expanded the development of digital medicine. Digital medicine refers to clinical evidence‐based technology and products with a direct impact on disease management and research. Integrating digital medicine into clinical practice has the advantages of broader applicability, greater cost‐effectiveness, better accessibility, and improved diagnostic and therapeutic performance. Digital medicine has emerged in different clinical application scenarios, including cancer prevention, screening, diagnosis, and treatment, as well as clinical trials. Additionally, big data generated from digital medicine can be used to improve levels of clinical diagnosis and treatment. However, digital medicine also faces many challenges, including security regulation and privacy protection, product usability, data management, and optimization of algorithms. In summary, the application and development of digital medicine in the field of cancer face numerous opportunities and challenges.

Background: An increasing number of cancer patients die of cardiovascular diseases. The cardiotoxicity of chemotherapy is particularly important in triple‐negative breast cancer (TNBC) with limited therapeutic options. Cardiac autophagy is an important mechanism of cardiotoxicity. This research was aimed to investigate the cardiotoxicity of chemotherapy in TNBC, screen the susceptible population, and determine the relationship between cardiotoxicity and autophagy‐related polymorphisms. Methods: From a total of 2450 stage I‐III TNBC patients, 147 met the inclusion criteria and finally recruited. Electrocardiography (ECG) was performed before most chemotherapy cycles, and echocardiography (UCG) was performed according to clinical needs. All ECG and UCG records were re‐interpreted by cardiologists at the National Center for Cardiovascular Disease, Fuwai Hospital. According to the National Center for Biotechnology Information and the Catalog of Somatic Mutations in Cancer database, we selected 25 single nucleotide polymorphisms (SNPs) related to autophagy and genotyped the 147 TNBC patients. Paired‐sample T tests, Chi squared tests, and logistic regression models were employed for the analysis. Results: Only 46 (31.3%) patients had normal ECG records after every chemotherapy cycle. Among the 16 patients who underwent UCG, 2 (12.5%) had a reversible decrease of left ventricular ejection fraction. The use of anthracyclines and excessive alcohol consumption were risk factors of ECG abnormalities. With the continuation of chemotherapy, heart rate gradually increased. Anthracyclines were associated with QRS duration abnormalities ( P = 0.043). After genotyping for 25 autophagy‐related SNPs, we found that the G allele of autophagy‐related 13 ( ATG13 ) rs10838611 was significantly associated with ECG abnormalities (odds ratio = 2.258, 95% confidence interval = 1.318–3.869; P = 0.003). Conclusion: ECG abnormalities caused by chemotherapy are common in the real world. Autophagy‐related SNPs are associated with chemotherapy‐induced cardiotoxicity, thereby providing new evidence for autophagy as a cause of chemotherapy‐induced cardiac damage.

Adenoid cystic carcinoma of the breast (ACCB) is a rare malignancy with a favorable prognosis. Little information exists regarding the impact of postoperative radiation therapy (RT) on survival outcome in patients with ACCB. This study aimed to evaluate the clinical significance of postoperative RT in ACCB. Data of patients with ACCB were extracted from the Surveillance, Epidemiology, and End Results database (2000–2019). Univariate and multivariable Cox regression analyses were performed to identify prognostic factors. In addition, a nomogram model was constructed and internally validated for discrimination and calibration. The value of postoperative RT was respectively accessed in each risk subgroup according to nomogram-deduced individualized score. A total of 689 eligible patients were included in the analysis. Partial mastectomy was associated with an increased risk of death compared with partial mastectomy plus postoperative RT (P = 0.020), but total mastectomy with or without postoperative RT was comparable (P = 0.624). Then, in-depth analysis was performed for patients receiving breast-conserving therapy (n = 485, the training set vs. the testing set = 340 vs. 145). Age at diagnosis, histological grade, and T stage were identified as prognostic factors for overall survival (OS) (All P < 0.05). A nomogram was constructed to provide predictive accuracy toward individual OS rates of ACCB and to divide patients into different risk subgroups. Notably, compared with non-RT, postoperative RT significantly improved OS in the high-risk subgroup (P = 0.006 for the training set, and P = 0.013 for the overall population) but not in the low-risk subgroup (P = 0.807 for the training set, and P = 0.293 for the overall population), suggesting that these patients may be able to exempt from postoperative RT. A robust and effective nomogram was developed to predict prognosis and assist in treatment decisions in patients with ACCB undergoing partial mastectomy.