Tumor drug resistance emerges from the interaction of two critical factors: tumor cellular heterogeneity and the immunosuppressive nature of the tumor microenvironment (TME). Tumor-associated macrophages (TAMs) constitute essential components of the TME. M2-like TAMs are essential in facilitating tumor metastasis as well as augmenting the drug resistance of tumors. This review encapsulates the mechanisms that M2-like TAMs use to promote tumor drug resistance. We also describe the emerging therapeutic strategies that are currently targeting M2-like TAMs in combination with other antitumor drugs, with some still undergoing clinical trial evaluation. Furthermore, we summarize and analyze various existing approaches for developing novel drugs that target M2-like TAMs to overcome tumor resistance, highlighting how targeting M2-like TAMs can effectively stop tumor growth, metastasis, and overcome tumor drug resistance.

To develop and validate a machine learning model incorporating dietary antioxidants to predict cardiovascular disease (CVD)-cancer comorbidity and to elucidate the role of antioxidants in disease prediction. Data were sourced from the National Health and Nutrition Examination Survey. Antioxidants, including vitamins, minerals, and polyphenols, were selected as key features. Additionally, demographic, lifestyle, and health condition features were incorporated to improve model accuracy. Feature preprocessing included removing collinear features, addressing class imbalance, and normalizing data. Models constructed within the mlr3 framework included recursive partitioning and regression trees, random forest, kernel k-nearest neighbors, naïve bayes, and light gradient boosting machine (LightGBM). Benchmarking provided a systematic approach to evaluating and comparing model performance. SHapley Additive exPlanation (SHAP) values were calculated to determine the prediction role of each feature in the model with the highest predictive performance. This analysis included 10,064 participants, with 353 identified as having comorbid CVD and cancer. After excluding collinear features, the machine learning model retained 29 dietary antioxidant features and 9 baseline features. LightGBM achieved the highest predictive accuracy at 87.9 %, a classification error rate of 12.1 %, and the top area under the receiver operating characteristic curve (0.951) and the precision-recall curve (0.930). LightGBM also demonstrated balanced sensitivity and specificity, both close to 88 %. SHAP analysis indicated that naringenin, magnesium, theaflavin, kaempferol, hesperetin, selenium, malvidin, and vitamin C were the most influential contributors. LightGBM exhibited the best performance for predicting CVD-cancer comorbidity. SHAP values highlighted the importance of antioxidants, with naringenin and magnesium emerging as primary factors in this model.

The CALLY index, which is derived from C-reactive protein (CRP) content, serum albumin level, and total lymphocyte count, reflects the immune, nutritional, and inflammatory status of the body. Lack of sufficient evidence on the correlation between the CALLY index and the prognosis of cancer patients with various cancer forms. This study seeks to elucidate the association between the CALLY index and mortality from all causes as well as specific causes in cancer patients within a U.S. population. This investigation encompassed 3511 cancer-afflicted adults from the National Health and Nutritional Examination Surveys (NHANES) spanning 1999 to 2018. The CALLY index was measured at baseline only. The relationship between the CALLY index and mortality from both all causes and cancer specifically was examined using Cox proportional hazards models. Additionally, restricted cubic spline, piecewise linear regression, and various subgroup and sensitivity analyses were employed. Over a median follow-up of 103 months, 1,355 deaths occurred, and the incidence of all-cause mortality for these participants was 38.34%. Our findings indicate that an elevated CALLY index correlates with a diminished risk of all-cause mortality. Upon applying a natural logarithmic transformation to the CALLY index, the comprehensively adjusted model revealed that each one-unit increment in ln CALLY corresponded to a 18% decrease in all-cause mortality risk among cancer patients (HR = 0.82, 95% CI:0.79–0.86). Analyses of mortality due to cardiac and cancer-related causes yielded consistent results, which were robust across various subgroup and sensitivity analyses. The CALLY index demonstrated a linear and negative association with all-cause mortality, as well as mortality caused by cancer and cardiac conditions, highlighting its significant prognostic value in patients with oncological conditions.

Yi-Fei-San-Jie Formula (YFSJF), a proprietary medicine of the First Affiliated Hospital of Guangzhou University of Chinese Medicine, has been widely used in clinical practice for several years and is currently being tested in randomized controlled trials for early-stage lung cancer in China. However, the mechanisms by which YFSJF affects lung cancer biology, particularly the immune microenvironment and metabolic processes, remain poorly understood. This study aims to explore how YFSJF modulates the immune microenvironment and metabolism in lung cancer, specifically its unique role in inhibiting immune evasion by targeting the TGR5/STAT3/PD-L1 pathway, which has not previously been reported. Computed Tomography (CT) scan was used to assess YFSJF efficacy in patients with lung cancer and a mouse model of urethane-induced lung cancer. Histopathological evaluation, flow cytometry, and metabolomic analysis were used to assess lung tissue structure, immune cell subset changes, and metabolism modulation, respectively. Western blotting and immunohistochemistry were used to detect Ki67, TTF-1, TGR5, STAT3, p-STAT3, and PD-L1 protein expression. Serum cytokines were detected by ELISA. YFSJF effectively reduced the size of human lung cancer lesions and decreased the tumor burden and improved survival rates in mice. Lung tissue structure was also improved after YFSJF treatment. YFSJF regulated T-cell subsets, particularly by downregulating cells with PD-1-positive expression of CD3⁺, CD4⁺, and CD8⁺, and elevated serum TNF-α, IFN-γ, and GzmB levels. In addition, YFSJF modulated bile acid metabolism, particularly by inhibiting deoxycholic acid metabolism, which participates in immune regulation in lung cancer by acting on the G protein-coupled bile acid receptor TGR5. Finally, YFSJF inhibited immune evasion by blocking the TGR5-mediated STAT3/PD-L1 pathway, weakening PD-L1 and PD-1 binding and reviving T-cell immune activity, thereby countering lung cancer immune evasion and exerting anti-tumor effects.

Qu-yu-jie-du (QYJD) decoction is an established traditional Chinese medicine (TCM) formulation. For over ten years, there has been empirical evidence in support of its benefits for colorectal cancer patients, yet RCT validation for it as a postoperative maintenance therapy is lacking. Despite achieving no evidence of disease (NED) status after curative-intent resection in metastatic colorectal cancer (mCRC), up to 60 % of patients relapse within five years, with no guideline-recommended maintenance therapy. To determine whether QYJD decoction improves disease-free survival (DFS) and modulates inflammation/lactate metabolism in postoperative mCRC-NED patients. In this single-center randomized trial, 140 stage IV mCRC patients achieving post-resection NED status were randomized at a ratio of 1:1 to either a QYJD group (200 mL/day for 2 years) or a control group (routine follow-up). Two patients per group withdrew consent prior to the intervention, resulting in an intention-to-treat (ITT) population of 136 patients (68 per group) for the final analysis. All received standard adjuvant chemotherapy. The primary outcome was DFS; secondary outcomes were OS, 1-/2-/3-year survival rates, adverse events, and inflammation/lactate metabolism markers. Compared to the control group, QYJD decoction significantly improved DFS throughout the observation period (HR = 0.515, p = 0.004). The 1-year DFS rate was 91.2 % (62/68) in the QYJD group versus 73.5 % (50/68) in the control group (p < 0.01); the 2-year DFS rate was 56.9 % (40/68) in the QYJD group versus 35.1 % (25/68) in the control group (p = 0.002); and the 3-year DFS rate was 47.4 % (32/68) in the QYJD group versus 32.4 % (22/68) in the control group (p = 0.03). Significant differences were observed across all time points (1-year, 2-year, and 3-year) for DFS. Regarding overall survival (OS), the 2-year OS rate was 95.4 % (65/68) in the QYJD group versus 85.1 % (58/68) in the control group (p = 0.01), and the 3-year OS rate was 68.7 % (47/68) in the QYJD group versus 57.7 % (39/68) in the control group (HR = 0.407, p = 0.019). QYJD also significantly reduced inflammatory markers and lactate dehydrogenase (LDH) (p < 0.05). The most common adverse events were grade 1 hematologic toxicity, anorexia, diarrhea, and nausea, which were generally mild and manageable. QYJD decoction significantly improves DFS and shows OS benefits in postoperative mCRC-NED patients. It also reduces systemic inflammation/LDH, and in terms of safety, only causes mild adverse events. Chinese Clinical Trial Registry (ChiCTR2100053521, registered on November 24, 2021).

Context The Xihuang pill (XHP) is a traditional Chinese medicine formulation that has been historically used in the prevention and treatment of proliferative breast diseases. However, there is a lack of guidelines that offer recommendations for its clinical use. Objective The task force from the Chinese Guangdong Pharmaceutical Association aims to develop evidence-based guidelines for XHP to prevent and treat proliferative breast diseases. Methods We searched six Chinese and English electronic databases, including the China National Knowledge Infrastructure, the Chinese Scientific Journal Database, the Wanfang Medical Database, PubMed, and Embase, up to November 1, 2022. Publications (case reports, clinical observation, clinical trials, reviews) on using XHP to treat proliferative breast diseases were manually searched. The search terms were Xihuang pill, hyperplasia of the mammary gland, breast lump, and mastalgia. The writing team developed recommendations based on the best available evidence. Results Treatment should be customized based on syndrome identification. We recommend using XHP for the prevention and treatment of breast hyperplasia disease when a patient presents the following syndromes: concurrent blood stasis syndrome, concurrent phlegm-stasis syndrome, and concurrent liver fire syndrome. Safety indicators, including blood analysis and liver and kidney function monitoring, should be performed regularly during treatment. Conclusions Current clinical evidence suggests that XHP can be used as a standalone treatment or in conjunction with other medications to prevent and manage breast hyperplasia diseases. More randomized controlled studies are warranted to establish high-quality evidence of its use.