Establishment Of A Gene Diagnostic Model For Distinguishing Ductal And Lobular Breast Carcinoma

Breast cancer is one of the most prevalent tumors and is the leading cause of cancer mortality among women.A growing body of work has found that addressing themolecular and clinical heterogeneity of breast carcinoma is necessary to determine effective treatment strategies.Furthermore,the morphology of breast tumors includes a variety of histology and molecular subtypes.Invasive ductal breast carcinoma(IDC)and invasive lobular breast carcinoma(ILC)are the main two pathologically defined groups of mammary malignances.These tumors are clinically distinct and accurate diagnosis is important in determining treatment.ILC is more frequently multifocal,bilateral and likely to metastasize tobone,peritoneum,and female reproductive system.In contrast,the lungs,pleura,and CNS were muchmore likely to be involved in advanced IDC.Despite the need to reliably distinguish these tumor types,there are no regularly employed molecular based classifiers for these two clinically distinct tumors.This study aimed to establish a gene expression based tool that can distinguish ILC and IDC and provide a molecular basis for the exploration of targeted therapeutic options and for improved prognostic outcome prediction.A total of 1845 invasive breast cancer cases in six cohorts were collected andsplit into discovery and validation cohorts.We analyzed whole genome expression data using shrunken centroids and elastic-net regularized linear modeling to define a set of 46 genes which could distinguish lobular from ductal tumors in both the discovery and validation cohorts.The distribution of model scores in the discovery and test cohorts with pathological diagnosis showed a strong association(p value < 0.0001 via T-test),with similar distributions in all cohorts.In the validation cohorts the concordance of predicted diagnosis with a pathological diagnosis was 92%.The pathological diagnosis has a greater association with grade than does thepredicted subtype(t value of-5.29;95%CI:-7.26,-3.34 vs.-3.39;95%CI:-5.36,-1.44 via ordered logisti cregression).A diagnostic tool was created that reliably distinguishes lobular from ductal carcinoma and breast carcinoma histopathology which has the potential to become a standardly employed tool for predicting prognostic outcome.This molecularly based model may also be useful in the exploration of targeted treatment strategies.ILC is less responsive to neoadjuvant chemotherapy,we can apply the model to cell lines to explore new effective compunds.