ABSTRACT
The purpose was to integrate clinicopathological and laboratory indicators to predict axillary nodal pathologic complete response (apCR) after neoadjuvant therapy (NAT). The pretreatment clinicopathological and laboratory indicators of 416 clinical nodal-positive breast cancer patients who underwent surgery after NAT were analyzed from April 2015 to 2020. Predictive factors of apCR were examined by logistic analysis. A nomogram was built according to logistic analysis. Among the 416 patients, 37.3% achieved apCR. Multivariate analysis showed that age, pathological grading, molecular subtype and neutrophil-to-lymphocyte ratio were independent predictors of apCR. A nomogram was established based on these four factors. The area under the curve (AUC) was 0.758 in the training set. The validation set showed good discrimination, with AUC of 0.732. In subtype analysis, apCR was 23.8, 47.1 and 50.8% in hormone receptor-positive/HER2-, HER2+ and triple-negative subgroups, respectively. According to the results of the multivariate analysis, pathological grade and fibrinogen level were independent predictors of apCR after NAT in HER2+ patients. Except for traditional clinicopathological factors, laboratory indicators could also be identified as predictive factors of apCR after NAT. The nomogram integrating pretreatment indicators demonstrated its distinguishing capability, with a high AUC, and could help to guide individualized treatment options.
Lay abstract The purpose of this study was to integrate more pretreatment indicators, including clinicopathological factors and simple laboratory indicators, to predict axillary nodal pathologic complete response (apCR) after neoadjuvant therapy for breast cancer. The authors collected the pretreatment clinicopathological factors and laboratory indexes of 416 nodal-positive patients with breast cancer. The authors then built a nomogram to predict the therapeutic effect in axillary lymph nodes. Among 416 patients, 37.3% (155 of 416) achieved apCR. The results showed that age, pathological grading, molecular subtype and neutrophil-to-lymphocyte ratio were independent predictors of apCR. Based on these four factors, a nomogram was then built. This nomogram helped to predict apCR. In addition to traditional clinicopathological factors, laboratory indicators were also identified as predictive factors of apCR after neoadjuvant therapy. Integrating pretreatment indicators might help to predict apCR and guide individualized treatment options.
Subject(s)
Biomarkers, Tumor/blood , Breast Neoplasms/therapy , Lymphatic Metastasis/diagnosis , Neoadjuvant Therapy/methods , Nomograms , Adult , Aged , Axilla , Breast Neoplasms/blood , Breast Neoplasms/diagnosis , Breast Neoplasms/pathology , Chemotherapy, Adjuvant/methods , Female , Fibrinogen/analysis , Humans , Lymph Node Excision , Lymph Nodes/drug effects , Lymph Nodes/pathology , Lymph Nodes/surgery , Lymphatic Metastasis/therapy , Mastectomy , Middle Aged , Neoplasm Grading , ROC Curve , Retrospective Studies , Treatment OutcomeABSTRACT
PURPOSE: The study aimed to explore whether the expression of lncRNAs in primary tumors could predict nodal efficacy after neoadjuvant therapy (NAT) for HER2+ breast cancer. METHODS: Total RNA was extracted from HER2+ breast cancer tissues before NAT (n=103) and from 48 pairs of cancers and para-cancers tissues that did not receive NAT. Different lncRNAs were selected by microarray, validated by qPCR, and analyzed to illuminate their potential as nodal efficacy biomarkers after NAT. RESULTS: Our results demonstrated that three lncRNA sets, lncRNA-AL390243.1, POTEH-AS1, and lncRNA-AC009975.1, were up-regulated in non-apCR tissues. The AUC value was 0.789 (95%CI: 0.703-0.876). The multivariate logistic regression analysis identified the expression of lncRNA-AL390243.1 (OR 5.143; 95% CI: 1.570-16.847), tumor type (OR 0.144; 95% CI: 0.024-0.855), and nodal stage (OR 0.507; 95% CI: 0.289-0.888) as independent predictors for apCR after NAT in HER2+ patients (all p<0.05). Then the three predictors were used to create a predictive nomogram. The AUC value was 0.859 (95%CI: 0.790-0.929). The calibration curve showed a satisfactory fit between predictive and actual observation based on internal validation with a bootstrap resampling frequency of 1000. Patients with higher expression of lncRNA-AL390243.1 had worse survival. LncRNA-AL390243.1 was up-regulated more in the nodal positive subgroup than in the nodal negative subgroup (p=0.0271). CONCLUSION: The lncRNA-AL390243.1, POTEH-AS1, and lncRNA-AC009975.1 were upregulated in non-apCR breast cancer tissues. These three lncRNAs might have the potential to be used as predictive biomarkers of nodal efficacy of HER2+ breast cancer. Further studies are required to illuminate the underlying molecular mechanisms further.
ABSTRACT
BACKGROUND: Exosomes derived from cancer cells encapsulate various kinds of tumor-specific molecules and thus can interact with adjacent or distant cells to mediate information exchange. Long non-coding RNAs (lncRNAs) in exosomes have the potential as diagnostic and prognostic biomarkers in different types of cancers. The current study was aimed to identify circulating exosomal lncRNAs for the diagnosis of colorectal cancer (CRC). METHODS: Exosomes were isolated from the serum by ultracentrifugation and verified by transmission electron microscope (TEM), qNano, and immunoblotting. Exosomal lncRNAs FOXD2-AS1, NRIR, and XLOC_009459 were selected by lncRNA microarray and validated by qPCR in 203 CRC patients and 201 healthy donors. The receiver operating characteristic curve (ROC) was used to assess the diagnostic efficiency of serum exosomal lncRNAs. RESULTS: Exosomal FOXD2-AS1, NRIR, and XLOC_009459 (TCONS_00020073) levels were significantly upregulated in 203 CRC patients and 80 early-stage CRC patients compared to 201 healthy donors, possessing the area under the curve (AUC) of 0.728, 0.660, and 0.682 for CRC, as well as 0.743, 0.660, and 0.689 for early-stage CRC, respectively. Notably, their combination demonstrated the markedly elevated AUC of 0.736 for CRC and 0.758 for early-stage CRC, indicating their potential as diagnostic biomarkers for CRC. CONCLUSIONS: Our data suggested that exosomal lncRNAs FOXD2-AS1, NRIR, and XLOC_009459 act as the promising biomarkers for the diagnostics of CRC and early-stage CRC.
ABSTRACT
IMPACT STATEMENT: The high mortality of non-small cell lung cancer (NSCLC) is mainly because the cancer has progressed to a more advanced stage before diagnosis. If NSCLC can be diagnosed at early stages, especially stage 0 or I, the overall survival rate will be largely improved by definitive treatment such as lobectomy. We herein validated two novel circulating serum ExmiRs as diagnostic biomarkers for early-stage NSCLC to fulfill the unmet medical need. Considering the number of specimens in this study, circulating serum exosomal miR-20b-5p and miR-3187-5p are putative NSCLC biomarkers, which need to be further investigated in a larger randomized controlled clinical trial.