The Daily Sign-Out

Possible false positive interpretation of Napsin A staining in evaluating lung non-small cell carcinomas

Dr. Nelson Ordonez (MD Anderson Cancer Center, Houston) published a brief and very helpful article in the March 2012 American Journal of Surgical Pathology (abstract) that addresses a very practical issue of using IHC staining for Napsin A in evaluating primary lung NSCLC for confirmation of adenocarcinoma type.

Napsin A is normally expressed in type II alveolar pneumocytes but may also be localized immunohistochemically in intraalveolar macrophages presumably from phagocytosis.  The expression of both Napsin A and pro-surfactant protein B (ProSP-B) are regulated by thyroid transcription factor-1 (TTF-1), which is one of the common IHC stains initially performed on NSCLC not diagnostic for adenocarcinoma on routine H&E.  Napsin A is localized to lamellar bodies with ProSP-B and is thought to be involved in post-translational processing of ProSP-B.

This paper must be understood in the context of new IASLC lung adenocarcinoma classification and the algorithm recommended to histological type NSCLC.  Napsin A has emerged as a useful adjunct IHC stain, such as, in those cases in which a tumor is negative or equivocal for initial screening markers for both adenocarcinoma (ADC) and squamous cell carcinoma (SQC).  Until recently, Napsin A was found to be highly specific for lung ADC.  But, as Dr. Ordonez points out, several recent publications have found Napsin A positivity in lung squamous cell carcinomas and, thus, cast doubt over the high degree of specificity of Napsin A for lung adenocarcinoma and utility of this marker in this context.

Dr. Ordonez studied Napsin A expression by IHC in 90 primary lung SQC, including whole section and biopsy specimens, and 64 non-pulmonary SQC.  None of the primary lung SQC or the non-pulmonary SQC showed Napsin A positive staining in the malignant cells.

The key observation is the identification of entrapped type 2 pneumocytes and/or intraalveolar macrophages in desmoplastic areas adjacent to the tumor and in small clusters within the tumor--which could be a source of false-positive interpretation in SQC.  Dr. Ordonez found 5 biopsies in which these entrapped cells were difficult to distinguish from malignant cells and CK 5/6 was used in 2 of these cases to rule out the possibility that these were Napsin A-positive malignant squamous cells.

This is a critical distinction and very welcome contribution to the lung cancer pathology literature.  The reader should keep point this in mind, especially when evaluating biopsy material.  The illustrations are excellent in demonstrating these points and should also be kept close at hand.  Congratulations to Dr. Nelson Ordonez for an excellent paper.

Biomarkers in COPD

Chronic obstructive lung disease (COPD) is defined functionally as airflow limitation that is not fully reversible.  It is a MAJOR cause of morbidity and mortality in the U.S. and worldwide.  COPD has two distinct major, but often coexisting, forms that represent different manifestations of COPD: emphysema and chronic bronchitis.  Emphysema can be defined morphologically, either by radiography or pathology, while chronic bronchitis is defined clinically based upon the duration of productive cough and exclusion of other causes.  Treatment is focused on preventing progression of disease and the development of acute exacerbations, which are a major cause of hospitalizations, morbidity and mortality.  Common to both major forms is small airways inflammation and an abnormal inflammatory response either in large airways (chronic bronchitis) or in alveoli (emphysema).

COPD is also associated with low-grade systemic inflammation and biomarkers that could predict increased risk for mortality from progressive disease or acute exacerbations might be greatly beneficial in providing more intesive surveillance and treatment of this group.  A team of researchers led by Tufts University School of Medicine screened blood samples from people in the ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) to see if inflammatory biomarkers could predict disease outcome (abstract).  The study included 1843 patients who were followed for 3 years.  168 of the 1843 patients (9.1%) died.  Serum or plasma levels of fibrinogen, chemokine ligand 18, surfactant protein D, C-reative protein, Clara cell secretory protein-16, interleukin-6, IL-8, and tumor necrosis factor-alpha were measured at recruitment and at subsequent visits.

The addtion of a panel of biomarkers significantly improved predictive power and was able to better predict outcomes compared with current clinical variables, including age, BODE index, and hospitalization history. The addition of IL-6 provided the most improvement of discriminatory power, but this was improved further with the addition of all biomarkers measured.

Medscape Interview with NIH Director

Medscape recently produced a fascinating interview with Dr. Francis Collins, Director of the National Intitutes of Health that focuses on genomics but ranges broadly over several areas, including medical education and preventative medicine.  It's not that long and there is also a text format if you don't want to watch the interview.  Highly recommended.  This a thought-provoking interview.

I think Dr. Collins is overly optimistic about the impact of genomics on day-to-day patient care.  Pharmacogenomics, for one example he uses, has not made any impact thus far in my experience.  While it is a tool, perhaps, for demonstrating why a patient may not be responding to a particular drug, the use of pharmacogenomic testing before initiating treatment has not been prospectively studied to my knowledge in any trials, for any drug.  This leaves aside the further studies regarding cost-benefit analyses as well as the issue of payment/reimbursement.  Right now, it seems cheaper and tried to put a patient on a standard dose and see what happens.

Another example is the idea of genomic sequencing of cancers.  It sounds good because it provides a "personalized" profile of a cancer.  What about tumor heterogeneity?  Do we sequence the primary tumor or metastasis?  Which part of the primary tumor?  Which metastasis?  Finally, how does one compare "unique" tumor genotypes and develop groups to statistically compare treatment responses?  At some point, patients have to be lumped together (and thus muddying up personalized differences) in order to find appropriate guidelines for treatment and provide some prognostic information.

Lots more to think about!