BACKGROUND: MicroRNA-1 (miR-1) is a tumour suppressor that can inhibit cell proliferation and invasion in several cancer types. In addition, miR-1 was found to be associated with drug sensitivity. Circulating miRNAs have been proven to be potential biomarkers with predictive and prognostic value. However, studies of miR-1 expression in the serum of breast cancer (BC) patients are relatively scarce, especially in patients receiving neoadjuvant chemotherapy (NAC).
METHODS: Serum samples from 80 patients were collected before chemotherapy, and RT-PCR was performed to detect the serum expression of miR-1. The correlation between miR-1 expression in serum and clinicopathological factors, including pathological complete response (pCR), was analyzed by the chi-squared test and logistic regression. KEGG and GSEA analysis were also performed to determine the biological processes and signalling pathways involved.
RESULTS: The miR-1 high group included more patients who achieved a pCR than did the miR-1 low group (p < 0.001). Higher serum miR-1 levels showed a strong correlation with decreased ER (R = 0.368, p < 0.001) and PR (R = 0.238, p = 0.033) levels. The univariate model of miR-1 for predicting pCR achieved an AUC of 0.705 according to the ROC curve. According to the interaction analysis, miR-1 interacted with Ki67 to predict the NAC response. According to the Kaplan-Meier plot, a high serum miR-1 level was related to better disease-free survival (DFS) in the NAC cohort. KEGG analysis and GSEA results indicated that miR-1 may be related to the PPAR signalling pathway and glycolysis.
CONCLUSIONS: In summary, our data suggested that miR-1 could be a potential biomarker for pCR and survival outcomes in patients with BC treated with NAC.

Paclitaxel and anthracycline-based chemotherapy is one of the standard treatment options for breast cancer. However, only about 6-30% of breast cancer patients achieved a pathological complete response (pCR), and the mechanism responsible for the difference is still unclear. In this study, random forest algorithm was used to screen feature genes, and artificial neural network (ANN) algorithm was used to construct an ANN model for predicting the efficacy of neoadjuvant chemotherapy for breast cancer. Furthermore, digital pathology, cytology, and molecular biology experiments were used to verify the relationship between the efficacy of neoadjuvant chemotherapy and immune ecology. It was found that paclitaxel and doxorubicin, an anthracycline, could induce typical pyroptosis and bubbling in breast cancer cells, accompanied by gasdermin E (GSDME) cleavage. Paclitaxel with LDH release and Annexin V/PI doubule positive cell populations, and accompanied by the increased release of damage-associated molecular patterns, HMGB1 and ATP. Cell coculture experiments also demonstrated enhanced phagocytosis of macrophages and increased the levels of IFN-γ and IL-2 secretion after paclitaxel treatment. Mechanistically, GSDME may mediate paclitaxel and doxorubicin-induced pyroptosis in breast cancer cells through the caspase-9/caspase-3 pathway, activate anti-tumor immunity, and promote the efficacy of paclitaxel and anthracycline-based neoadjuvant chemotherapy. This study has practical guiding significance for the precision treatment of breast cancer, and can also provide ideas for understanding molecular mechanisms related to the chemotherapy sensitivity.

BACKGROUND: To assess the feasibility and diagnostic performance of the fractional order calculus (FROC), continuous-time random-walk (CTRW), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), mono-exponential (MEM) and stretched exponential models (SEM) for predicting response to neoadjuvant chemotherapy (NACT) in patients with esophageal squamous cell carcinoma (ESCC).
METHODS: This study prospectively included consecutive ESCC patients with baseline and follow up MR imaging and pathologically confirmed cT1-4aN + M0 or T3-4aN0M0 and underwent radical resection after neoadjuvant chemotherapy (NACT) between July 2019 and January 2023. Patients were divided into pCR (TRG 0) and non-pCR (TRG1 + 2 + 3) groups according to tumor regression grading (TRG). The Pre-, Post- and Delta-treatment models were built. 18 predictive models were generated according to different feature categories, based on six models by five-fold cross-validation. Areas under the curve (AUCs) of the models were compared by using DeLong method.
RESULTS: Overall, 90 patients (71 men, 19 women; mean age, 64 years ± 6 [SD]) received NACT and underwent baseline and Post-NACT esophageal MRI, with 29 patients in the pCR group and 61 patients in the non-pCR group. Among 18 predictive models, The Pre-, Post-, and Delta-CTRW model showed good predictive efficacy (AUC = 0.722, 0.833 and 0.790). Additionally, the Post-FROC model (AUC = 0.907) also exhibited good diagnostic performance.
CONCLUSIONS: Our study indicates that the CTRW model, along with the Post-FROC model, holds significant promise for the future of NACT efficacy prediction in ESCC patients.

BACKGROUND: Sarcopenic obesity (SO) affects outcomes in various malignancies. However, its clinical significance in patients undergoing neoadjuvant chemotherapy (NAC) for locally advanced gastric cancer (LAGC) remains unclear. This study investigated the impact of pre- and post-NAC SO on postoperative morbidity and survival.
METHODS: Data from 207 patients with LAGC, who underwent NAC followed by radical gastrectomy between January 2010 and October 2019, were reviewed. Skeletal muscle mass and visceral fat area were measured pre- and post-NAC using computed tomography to define sarcopenia and obesity, the coexistence of which was defined as SO.
RESULTS: Among the patients, 52 (25.1%) and 38 (18.4%) developed SO before and after NAC, respectively. Both pre- (34.6%) and post- (47.4%) NAC SO were associated with the highest postoperative morbidity rates; however, only post-NAC SO was an independent risk factor for postoperative morbidity [hazard ratio (HR) = 9.550, 95% confidence interval (CI) = 2.818-32.369; P < .001]. Pre-NAC SO was independently associated with poorer 3-year overall [46.2% vs. 61.3%; HR = 1.258 (95% CI = 1.023-1.547); P = .049] and recurrence-free [39.3% vs. 55.4%; HR 1.285 (95% CI 1.045-1.579); P = .017] survival.
CONCLUSIONS: Pre-NAC SO was an independent prognostic factor in patients with LAGC undergoing NAC; post-NAC SO independently predicted postoperative morbidity.

OBJECTIVE: To investigate the serum lipid profiles of patients with localized osteosarcoma around the knee joint before and after neoadjuvant chemotherapy.
METHODS: After retrospectively screening the data of 742 patients between January 2007 and July 2020, 50 patients aged 13 to 39 years with Enneking stage II disease were included in the study. Serum lipid levels, including total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), lipoprotein-α [Lp(a)], and apolipoprotein A1, B, and E (ApoA1, ApoB, and ApoE), and clinicopathological characteristics were collected before and after neoadjuvant chemotherapy.
RESULTS: The mean levels of TC, TG, and ApoB were significantly increased following neoadjuvant chemotherapy (16%, 38%, and 20%, respectively, vs. pretreatment values; P<0.01). The mean levels of LDL-C and ApoE were also 19% and 16% higher, respectively (P<0.05). No correlation was found between the pretreatment lipid profile and the histologic response to chemotherapy. An increase in Lp(a) was strongly correlated with the Ki-67 index (R=0.31, P=0.023). Moreover, a trend toward longer disease-free survival (DFS) was observed in patients with decreased TG and increased LDL-C following chemotherapy, although this difference was not statistically significant (P=0.23 and P=0.24, respectively).
CONCLUSIONS: Significant elevations in serum lipids were observed after neoadjuvant chemotherapy in patients with localized osteosarcoma. There was no prognostic significance of pretreatment serum lipid levels on histologic response to neoadjuvant chemotherapy. The scale of increase in serum Lp(a) might have a potential prognostic role in osteosarcoma. Patients with increased LDL-C or reduced TG after chemotherapy seem to exhibit a trend toward favorable DFS.

UNASSIGNED: To investigate the association between lipid ratios and survival outcomes in patients with locally advanced breast cancer (LABC) undergoing neoadjuvant chemotherapy.
UNASSIGNED: This retrospective study included patients with LABC receiving neoadjuvant chemotherapy. Serum lipid levels were prospectively measured at baseline. Associations of triglyceride to total cholesterol (TG/TC), triglyceride to high-density lipoprotein (TG/HDL) and triglyceride to low-density lipoprotein (TG/LDL) ratios with prognosis were evaluated.
UNASSIGNED: Patients with high TG/TC (adjusted hazard ratio [aHR] = 2.47, 95% CI: 1.10, 5.56, p = 0.029), TG/HDL (aHR = 2.73, 95% CI: 1.16, 6.41, p = 0.021) and TG/LDL (aHR = 2.50, 95% CI: 1.11, 5.65, p = 0.027) ratios were more likely to experience disease-free survival (DFS) events. Subgroup analysis suggested that the prognostic impact of lipid ratios was more pronounced in patients with negative HER2 status or those at a high risk of recurrence (e.g. clinical stage III, Ki67 > 30%). Additionally, higher lipid ratios tended to indicate early DFS events (0 ~ 2 years) (TG/TC p = 0.021, TG/HDL p = 0.046, TG/LDL p < 0.001), and the TG/LDL ratio demonstrated the best predictive efficacy (TG/TC vs. TG/HDL vs. TG/LDL, 1-year AUC: 0.724 vs. 0.676 vs. 0.846, 2-year AUC: 0.653 vs. 0.638 vs. 0.708).
UNASSIGNED: Baseline serum TG/TC, TG/HDL and TG/LDL ratios were independent prognostic factors in patients with LABC undergoing neoadjuvant therapy. However, their utility in predicting the early DFS events warrants further investigation.
UNASSIGNED: NCT05621564.

It is crucial to decipher the modulation of regulatory T cells (Tregs) in tumor microenvironment (TME) induced by chemotherapy, which may contribute to improving the efficacy of neoadjuvant chemoimmunotherapy in resectable non-small cell lung cancer (NSCLC). We retrospectively collected specimens from patients with II-III NSCLC, constituting two cohorts: a neoadjuvant chemotherapy (NAC) cohort (N = 141) with biopsy (N = 58) and postoperative specimens (N = 141), and a surgery-only cohort (N = 122) as the control group. Then, the cell density (Dens), infiltration score (InS), and Treg-cell proximity score (TrPS) were conducted using a panel of multiplex fluorescence staining (Foxp3, CD4, CD8, CK, CD31, ɑSMA). Subsequently, the association of Tregs with cancer microvessels (CMVs) and cancer-associated fibroblasts (CAFs) was analyzed. Patients with NAC treatment have a higher density of Tregs in both paired (P < 0.001) and unpaired analysis (P = 0.022). Additionally, patients with NAC treatment showed higher infiltration score (paired, P < 0.001; unpaired, P = 0.014) and more CD8+T cells around Tregs (paired/unpaired, both P < 0.001). Subgroup analysis indicated that tumors with a diameter of ≤ 5 cm exhibited increase in both Dens(Treg) and InS(Treg), and gemcitabine, pemetrexed and taxel enhanced Dens(Treg) and TrPS(CD8) following NAC. Multivariate analysis identified that the Dens(Tregs), InS(Tregs) and TrPS(CD8) were significantly associated with better chemotherapy response [OR = 8.54, 95%CI (1.69, 43.14), P = 0.009; OR = 7.14, 95%CI (1.70, 30.08), P = 0.024; OR = 5.50, 95%CI (1.09, 27.75), P = 0.039, respectively] and positive recurrence-free survival [HR = 3.23, 95%CI (1.47, 7.10), P = 0.004; HR = 2.70; 95%CI (1.27, 5.72); P = 0.010; HR = 2.55, 95%CI (1.21, 5.39), P = 0.014, respectively]. Moreover, TrPS(CD8) and TrPS(CD4) were negatively correlated with the CMVs and CAFs. These discoveries have deepened our comprehension of the immune-modulating impact of chemotherapy and underscored that the modified spatial landscape of Tregs after chemotherapy should be taken into account for personalized immunotherapy, aiming to ultimately improve clinical outcomes in patients with NSCLC.

BACKGROUND: Previous studies have shown that the addition of platinum to neoadjuvant chemotherapy (NAC) improved outcomes for patients with triple-negative breast cancer (TNBC). However, no studies have assessed the efficacy and safety of the combination of taxane and lobaplatin. In this study, we conducted a randomized controlled phase II clinical study to compare the efficacy and safety of taxane combined with lobaplatin or anthracycline.
METHODS: We randomly allocated patients with stage I-III TNBC into Arm A and Arm B. Arm A received six cycles of taxane combined with lobaplatin (TL). Arm B received six cycles of taxane combined with anthracycline and cyclophosphamide (TEC) or eight cycles of anthracycline combined with cyclophosphamide and sequential use of taxane (EC-T). Both Arms underwent surgery after NAC. The primary endpoint was the pathologic complete response (pCR). Secondary endpoints were event-free survival (EFS), overall survival (OS), and safety.
RESULTS: A total of 103 patients (51 in Arm A and 52 in Arm B) were assessed. The pCR rate of Arm A was significantly higher than that of Arm B (41.2% vs. 21.2%, P = 0.028). Patients with positive lymph nodes and low neutrophil-to-lymphocyte ratio (NLR) benefited significantly more from Arm A than those with negative lymph nodes and high NLR (Pinteraction = 0.001, Pinteraction = 0.012, respectively). There was no significant difference in EFS (P = 0.895) or OS (P = 0.633) between the two arms. The prevalence of grade-3/4 anemia was higher in Arm A (P = 0.015), and the prevalence of grade-3/4 neutropenia was higher in Arm B (P = 0.044).
CONCLUSIONS: Neoadjuvant taxane plus lobaplatin has shown better efficacy than taxane plus anthracycline, and both regimens have similar toxicity profiles. This trial may provide a reference for a better combination strategy of immunotherapy in NAC for TNBC in the future.

OBJECTIVE: To determine whether MRI can predict the necessity of rectosigmoid resection (RR) for optimal debulking surgery (ODS) in ovarian cancer (OC) patients and to compare the predictive accuracy of pre- and post-neoadjuvant chemotherapy (NACT) MRI.
METHODS: The MRI of 82 OC were retrospectively analyzed, including six bowel signs (length, transverse axis, thickness, circumference, muscularis involvement, and submucosal edema) and four para-intestinal signs (vaginal, parametrial, ureteral, and sacro-recto-genital septum involvement). The parameters reflecting the degree of muscularis involvement were measured. Patients were divided into non-RR and RR groups based on the operation and postoperative outcomes. The independent predictors of the need for RR were identified by multivariate logistic regression analysis.
RESULTS: Imaging for 82 patients was evaluated (67 without and 15 with NACT). Submucosal edema and muscularis involvement (OR 13.33 and 8.40, respectively) were independent predictors of the need for RR, with sensitivities of 83.3% and 94.4% and specificities of 93.9% and 81.6%, respectively. Among the parameters reflecting the degree of muscularis involvement, circumference ≥ 3/12 had the highest prediction accuracy, increasing the specificity from 81.6% for muscularis involvement only to 98.0%, with only a slight decrease in sensitivity (from 94.4% to 88.9%). The predictive sensitivities of pre-NACT and post-NACT MRI were 100.0% and 12.5%, respectively, and the specificities were 85.7% and 100.0%, respectively.
CONCLUSIONS: MRI analysis of rectosigmoid muscularis involvement and its circumference can help predict the necessity of RR in OC patients, and pre-NACT MRI may be more suitable for evaluation.
UNASSIGNED: We analyzed preoperative pelvic MRI in OC patients. Our findings suggest that MRI has predictive potential for identifying patients who require RR to achieve ODS.
CONCLUSIONS: The need for RR must be determined to optimize treatment for OC patients. Muscularis involvement circumference ≥ 3/12 could help predict RR. Pre-NACT MRI may be superior to post-NACT MRI in predicting RR.

This study aims to create and assess machine learning models for predicting lymph node metastases following neoadjuvant treatment in advanced gastric cancer (AGC) using baseline and restaging computed tomography (CT). We evaluated CT images and pathological data from 158 patients with resected stomach cancer from two institutions in this retrospective analysis. Patients were eligible for inclusion if they had histologically proven gastric cancer. They had received neoadjuvant chemotherapy, with at least 15 lymph nodes removed. All patients received baseline and preoperative abdominal CT and had complete clinicopathological reports. They were divided into two cohorts: (a) the primary cohort (n = 125) for model creation and (b) the testing cohort (n = 33) for evaluating models\' capacity to predict the existence of lymph node metastases. The diagnostic ability of the radiomics-model for lymph node metastasis was compared to traditional CT morphological diagnosis by radiologist. The radiomics model based on the baseline and preoperative CT images produced encouraging results in the training group (AUC 0.846) and testing cohort (AUC 0.843). In the training cohort, the sensitivity and specificity were 81.3% and 77.8%, respectively, whereas in the testing cohort, they were 84% and 75%. The diagnostic sensitivity and specificity of the radiologist were 70% and 42.2% (using baseline CT) and 46.3% and 62.2% (using preoperative CT). In particular, the specificity of radiomics model was higher than that of conventional CT in diagnosing N0 cases (no lymph node metastasis). The CT-based radiomics model could assess lymph node metastasis more accurately than traditional CT imaging in AGC patients following neoadjuvant chemotherapy.