Early detection and diagnosis of many cancers is very challenging. Late stage detection of a cancer always leads to high mortality rates. It is imperative to develop novel and more sensitive and effective diagnosis and therapeutic methods for cancer treatments. The development of new cancer treatments has become a crucial aspect of medical advancements. Nanobots, as one of the most promising applications of nanomedicines, are at the forefront of multidisciplinary research. With the progress of nanotechnology, nanobots enable the assembly and deployment of functional molecular/nanosized machines and are increasingly being utilized in cancer diagnosis and therapeutic treatment. In recent years, various practical applications of nanobots for cancer treatments have transitioned from theory to practice, from in vitro experiments to in vivo applications. In this paper, we review and analyze the recent advancements of nanobots in cancer treatments, with a particular emphasis on their key fundamental features and their applications in drug delivery, tumor sensing and diagnosis, targeted therapy, minimally invasive surgery, and other comprehensive treatments. At the same time, we discuss the challenges and the potential research opportunities for nanobots in revolutionizing cancer treatments. In the future, medical nanobots are expected to become more sophisticated and capable of performing multiple medical functions and tasks, ultimately becoming true nanosubmarines in the bloodstream.Graphical abstract

Objective: Prognostic nutritional index (PNI), calculated as serum albumin (ALB) (g/L) + 5 × total lymphocyte count (10⁹/L), is initially used to evaluate nutritional status in patients undergoing surgery and may evaluate the therapeutic effects and predict the survival of various solid tumors. The present study aimed to evaluate the potential prognostic significance of PNI in breast cancer patients receiving neoadjuvant chemotherapy (NACT).Methods: A total of 785 breast cancer patients treated with neoadjuvant chemotherapy were enrolled in this retrospective study. The optimal cutoff value of PNI by receiver operating characteristic curve stratified patients into a low-PNI group (<51) and a high PNI group (≥51). The associations between breast cancer and clinicopathological variables by PNI were determined by chi-square test or Fisher’s exact test. Kaplan–Meier plots and log-rank test were used to evaluate the clinical outcomes of disease-free survival (DFS) and overall survival (OS). The prognostic value of PNI was analyzed by univariate and multivariate Cox proportional hazards regression models. The toxicity of NACT was accessed by the National Cancer Institute Common Toxicity Criteria (NCI-CTC).Results: The results indicated that PNI had prognostic significance by an optimal cutoff value of 51 on DFS and OS in univariate and multivariate Cox regression survival analyses. Breast cancer patients with a high PNI value had longer DFS and OS than those with a low PNI value [47.64 vs. 36.60 months, P < 0.0001, hazard ratio (HR) = 0.264, 95%CI = 0.160–0.435; 73.61 vs. 64.97 months, P < 0.0001, HR = 0.319, 95%CI = 0.207–0.491, respectively]. Furthermore, the results indicated that patients with high PNI had longer DFS and OS than those with low PNI in early stage and advanced breast cancer, especially in advanced breast cancer. The mean DFS and OS times for breast cancer patients with high PNI by the log-rank test were longer than in those with low PNI in different molecular subtypes. Moreover, the mean DFS and OS times in patients with high PNI by the log-rank test were longer than in those patients with low PNI without or with lymph vessel invasion. The common toxicities after neoadjuvant chemotherapy were hematologic and gastrointestinal reaction, and the PNI had no significance on the toxicities of all enrolled patients, except in anemia, leukopenia, and myelosuppression.Conclusion: Pretreatment PNI with the advantages of being convenient, noninvasive, and reproducible was a useful prognostic indicator for breast cancer patients receiving neoadjuvant chemotherapy and is a promising biomarker for breast cancer on treatment strategy decisions.

Breast cancer is the most commonly diagnosed cancer and the leading cause of death in women worldwide.^1,2 Despite recent advances in treatment and prognosis of this disease, the racial/ethnic gap in incidence and death rates has widened. In the United States, the incidence of breast cancer is higher among Black and White individuals younger than 45 years, whereas the rate in White women between the ages of 60 and 84 years is substantially higher than in Black women.³ Although the incidence in Black women is lower, the mortality rate is higher in Black women than in White women.^4,5 A propensity-matched study using the National Cancer Data Base reported that, among female patients with hormone receptor (HR)–positive breast cancer, Black women had twice the risk of death compared with White women.⁶ Miller et al⁷ reported that, in a study of more than 1.3 million women in the US who were diagnosed with breast cancer between 2001 and 2009, the survival rate for Black women was consistently 10 percentage points lower than for White women, and this disparity persisted over time.

Around one sixth of breast cancer cases are classified as triple-negative breast cancer (TNBC), named after the absence of the expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2); however, patients with TNBC suffer from poor clinical outcome and shortage of targeted therapy. Genistein, an estrogenic soy isoflavone, shows anticancer effects in TNBC cells such as inducing G2/M cell cycle arrest and apoptosis. However, the underlying mechanism of its anticancer effects is poorly understood and its elucidation can help the development of novel therapeutic strategies for TNBC. In this study, by combining isobaric tag-based TMT labeling with titanium dioxide-based phosphopeptide enrichment, we quantitated 5,445 phosphorylation sites on 2,008 phosphoproteins in the TNBC cell line MDA-MB-231, upon genistein treatment. Our analysis revealed 332 genistein-regulated phosphorylation sites on 226 proteins. Our data show that genistein can regulate several biological processes during the cell cycle, including DNA replication, cohesin complex cleavage, and kinetochore formation. Furthermore, genistein can also activate DNA damage response, including activation of ATR and BRCA1 complex. Overall, our study presents evidence at a phosphoproteomic level that genistein is able to inhibit TNBC cell growth by regulating the cell cycle and DNA damage response in a more complex manner. Our findings help elucidate the mechanisms through which genistein exerts its anticancer effects in TNBC cells.

There is a close relationship between inflammatory cells and tumors, but the pathways that connect the two remain unclear. This research explores the clinical and prognostic value of the systemic inflammation response index (SIRI) in breast cancer patients. The study included 477 breast cancer patients who underwent neoadjuvant chemotherapy and 308 breast cancer patients who did not in our center between January 1998 and December 2016. Optimal SIRI threshold values were determined using the receiver operating characteristic curve (ROC). Patients were then reclassified as SIRI ≥0.80 group (High SIRI group) and SIRI <0.80 group (Low SIRI group). The outcomes were analyzed by statistical methods. The univariate and multivariate analyses demonstrated that SIRI independently predicted survival in breast cancer. The disease-free survival (DFS) and overall survival (OS) in patients with low SIRI scores were significantly longer in contrast to those with high SIRI scores (41.50 vs. 37.63 months, and 64.57 vs. 58.42 months). Further subgroup analyses revealed that low SIRI score patients who also had either early breast cancer, advanced breast cancer, or different molecular subtypes also possessed longer mean survival time of DFS and OS in contrast to those with high SIRI levels (χ2 = 2.379, p = 0.123, and χ2 = 5.153, p = 0.023; χ2 = 11.080, p = 0.0009 and χ2 = 15.900, p < 0.0001; χ2 = 16.020, p < 0.0001 and χ2 = 22.050, p < 0.0001, respectively). SIRI serves as an easily accessible, replicable, and minimally invasive prognostic tool in breast cancer patients. Lower SIRI scores were predictive of a longer DFS and OS after surgery in breast cancer patients. SIRI may serve as a marker to guide clinical management and prognostication of breast cancer.