New Approach To Identifying Informative Autoantibodies Associated With Lung Cancer

Recently, construction of tumor cell cDNA libraries and screening using autologous host sera (SEREX) has revealed that a B-cell response to tumor antigens is more prevalent than previously observed [28-32], The success of this methodology is likely attributable to enriching for cDNA expressed by the autologous tumor. This enrichment no doubt facilitates the identification and cloning of antigens corresponding to autoantibodies in the autologous sera, which may be relatively rare or nonexistent in expression libraries made from cancer cell lines or other nonautologous cells. This established method may also preferentially identify autoantigens that are overexpressed, rather than mutated, in tumor cells. Indeed, while SEREX has identified some mutational antigens, the majority of SEREX antigens appear to be overexpressed, but otherwise normal antigens [32], In addition, SEREX methodology alone does not select for antigens that are oncogenic.

We have devised an alternative strategy to identify autoantigens associated with lung cancer, with the goal of first focusing our attention on those that have the most potential to be informative. Our method first aims to identify the antinuclear autoantibodies that show significant association with diagnosis, cancer cell type, or patient outcome. Once identified, nuclear antigens can be cloned from either a HeLa cDNA library, the most appropriate lung cell library, or in combination with the SEREX approach, from a library constructed from autologous tumor cDNA.

We have chosen to screen populations of patient sera for reactivity on immunoblots of nuclear proteins derived from all four types of lung cell cancers, as well as from normal lung cell and HeLa cells. This maximizes the probability of detecting antigens associated with a given type of cancer, while minimizing detection of antigens that are specific to one individual's tumor.

All reactivities are catalogued by estimated molecular mass and antigen type, and subsequently analyzed by classification and regression tree analysis (CART) [52, 53]. Unique reactivities are defined as antibody reactivities associated with only one antigen type. Associations are then sought between individual or groups of unique reactivities and the presence or absence of cancer, cancer cell type, and prognosis.

In a pilot study, the sera of 64 lung cancer patients and 64 subjects without a history of cancer were retrospectively tested for reactivity on immunoblots of nuclear extracts of HeLa, small cell carcinoma, squamous cell carcinoma, adenocarcinoma, large cell carcinoma of the lung and normal lung cells [54], Demographics as well as clinical characteristics of these groups have been reported [55], All IgG and IgM reactivities detectable on immunoblots at a 1:500 dilution of the sera were recorded and antigen molecular masses were calculated by comparison to molecular weight standards. We found that a sizable proportion of lung cancer sera show unique nuclear reactivity under similar conditions (see Fig. 1).

Even with this relatively small data set, we were able to identify antinuclear antibodies that had significant predictive ability for all three parameters. Statistical analyses using cross-validated CART suggested that immunoblots using a battery of nuclear antigen sets may reveal some degree of tumor specificity and that groups of nuclear antigens recognized by autoantibodies have the potential to discriminate among dif-

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