Trial Information

Study of Prognostic Value of T Cell Receptor Diversity and CD4 Lymphopenia in First Relapse Breast or Lung Cancer Patients

The therapeutic management recommendations of patients with metastatic cancer offer standard
treatment in specific situations. But, there is always a subgroup of patients who do not
benefit from treatment and which has a very low survival. The risk of death for patients is
very variable depending on the initial cancer site, tumor aggressiveness and
chemosensitivity of tumours.

It's therefore important to have relevant prognostic tools to predict such an excess of
relative toxicity or drug resistance. Simple prognostic factors for survival as the
performance status (PS) have already been highlighted in several studies. Thus, the
possibility to identify a group of patients with a higher risk of mortality could be of
major interest for clinicians. In fact such stratification will allow:

- To limit this risk by adjusting the therapy and/or associated treatments (antibiotic
prophylaxis, dose reduction ...),

- To develop protocols for testing innovative strategies specific to this high risk
population.

The objectives of these innovative protocols would be designed to correct lymphodivpenia.

The main objective is to show that T divpenia (low TCR combinatorial diversity <30%) is a
risk factor for early death after chemotherapy (early death: any death occurring within 3
months (lung cancer) or within 6 months (breast cancer) after the start of chemotherapy).

The secondary objectives are:

- To establish that the divpenia factor is independent of clinical and biological
prognostic factors (PS, LDH, haemoglobin, lymphopenia or ANC) to predict a early death,

- To establish that the prognostic score NDL which will combine in a two-dimensional
graph the CD4 count or total lymphocytes count and TCR repertoire diversity will allow
a better stratification of lympho-divpenic patients who will benefit from more
appropriate treatments,

- To characterize other circulating markers this could improve the identification of the
early death risk (phenotypic markers, cytokines ...) in combination with the previous
settings.

Prognostic models have been established in many tumor types at the initial stage or at time
of the relapse (breast and lung cancers ...). It seems necessary to highlight other clinical
and biological prognostic factors that would estimate a lower survival at 6 months, whatever
the nature or the original site of the tumour.

The strong prognostic value of lymphopenia in the early death after chemotherapy or
hematologic toxicity of chemotherapy has recently been established in several tumor models.
25% of patients with metastatic solid cancers have a systemic immune dysfunction.

Further analysis incorporating prior any treatment (D0) a systematic phenotypic analysis of
lymphocyte subpopulations in the patients' blood showed that a significant reduction in the
absolute number of peripheral CD4+ T cells (<450/μl) was an independent factor risk of early
death and febrile neutropenia in patients with solid cancers of different origin (lymphoma,
myeloma, sarcoma, breast cancer) treated with chemotherapy.

However, early death remains rare events and a more recent study has established that a
lymphopenia (<1000 lymphocytes/µl) was an independent prognostic factor for overall survival
in patients with solid tumours.

Recent studies have shown the importance of combinatorial diversity of T and B lymphocytes
repertoire (TCR/BCR) in the efficiency of the immune response against infection.

A preliminary analysis of TCR repertoire diversity, in a retrospective cohort of patients
with metastatic breast cancer, demonstrated the independent predictive value of divpenia for
overall survival in these patients. This research has demonstrated that patients with cancer
had a very large disparity in immune TCR diversity and that it was not always correlated
with lymphocyte count.

These preliminary data show that the discriminating power of TCR diversity is greater than
the measurement of cell count. The combined analysis of these data in a NDL® graph may help
to better discriminate patients at risk for which it is necessary to develop new therapeutic
strategies.