Diagnostic and prognostic implications of a three-antibody molecular subtyping algorithm for non-muscle invasive bladder cancer.
Chelsea L JacksonLina ChenCéline Sc HardyKevin Ym RenKash VisramVanessa F BrattiJeannette JohnstoneGottfrid SjödahlDavid Robert SiemensRobert J GoodingDavid M BermanPublished in: The journal of pathology. Clinical research (2021)
Intrinsic molecular subtypes may explain marked variation between bladder cancer patients in prognosis and response to therapy. Complex testing algorithms and little attention to more prevalent, early-stage (non-muscle invasive) bladder cancers (NMIBCs) have hindered implementation of subtyping in clinical practice. Here, using a three-antibody immunohistochemistry (IHC) algorithm, we identify the diagnostic and prognostic associations of well-validated proteomic features of basal and luminal subtypes in NMIBC. By IHC, we divided 481 NMIBCs into basal (GATA3- /KRT5+ ) and luminal (GATA3+ /KRT5 variable) subtypes. We further divided the luminal subtype into URO (p16 low), URO-KRT5+ (KRT5+ ), and genomically unstable (GU) (p16 high) subtypes. Expression thresholds were confirmed using unsupervised hierarchical clustering. Subtypes were correlated with pathology and outcomes. All NMIBC cases clustered into the basal/squamous (basal) or one of the three luminal (URO, URO-KRT5+ , and GU) subtypes. Although uncommon in this NMIBC cohort, basal tumors (3%, n = 16) had dramatically higher grade (100%, n = 16, odds ratio [OR] = 13, relative risk = 3.25) and stage, and rapid progression to muscle invasion (median progression-free survival = 35.4 months, p = 0.0001). URO, the most common subtype (46%, n = 220), showed rapid recurrence (median recurrence-free survival [RFS] = 11.5 months, p = 0.039) compared to its GU counterpart (29%, n = 137, median RFS = 16.9 months), even in patients who received intravesical immunotherapy (p = 0.049). URO-KRT5+ tumors (22%, n = 108) were typically low grade (66%, n = 71, OR = 3.7) and recurred slowly (median RFS = 38.7 months). Therefore, a simple immunohistochemical algorithm can identify clinically relevant molecular subtypes of NMIBC. In routine clinical practice, this three-antibody algorithm may help clarify diagnostic dilemmas and optimize surveillance and treatment strategies for patients.
Keyphrases
- muscle invasive bladder cancer
- free survival
- machine learning
- clinical practice
- low grade
- deep learning
- early stage
- spinal cord injury
- healthcare
- end stage renal disease
- skeletal muscle
- transcription factor
- poor prognosis
- public health
- working memory
- neural network
- primary care
- quality improvement
- cell therapy
- mesenchymal stem cells
- metabolic syndrome
- bone marrow
- single cell
- radiation therapy
- chronic kidney disease
- sentinel lymph node
- patient reported outcomes
- locally advanced