Introduction: Although expression of β1 integrins was analyzed in B-cell chronic lymphocytic leukemia (B-CLL), little is known about the clinical behaviour and the phenotyic profile of B-CLLs with different patterns of β1 integrin expression.

Methods: Expression of β1 integrins (α1-α6) was investigated by flow cytometry along with other 30 surface molecules (B-cell markers, cell-adhesion-molecules, activation inducers, complement activity regulators) in 155 B-CLLs, 106 characterized for clinical stage (Rai’s stages), 121 for IgVH mutations, 79 for ZAP-70 expression and 109 with survival data.

Results: In agreement with previous studies, also in our B-CLL series CD49c, CD49d and, to a lesser extent, CD49e resulted the most expressed β1 integrins, with mean expression values, evaluated as % of positive cells, of 59%, 36% and 26% (range 1-100%), respectively. Since expression of CD49c and CD49d have been recently identified by us as part of the immunophenotypic signatures of B-CLLs with different prognosis (

J Cell Physiol
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2005
), the present study was designed to define: 1) the real prognostic impact and the optimal cutoffs for CD49c and CD49d splitting patients into two groups with different survivals; 2) the immunophenotypic and molecular features of B-CLL subsets expressing different levels of CD49c and CD49d. 1) By applying the maximally selected log-rank statistics, we identified cutoff values of 40% and 30% of positive cells for CD49c and CD49d, respectively; therefore, B-CLL cases were divided in CD49chigh or CD49clow and CD49dhigh or CD49dlow if the expression of the molecules was above or below their respective cutoffs. The CD49chigh B-CLL subset (n=78) displayed longer survival as compared to CD49clow cases (n=31; p=2.0x10-2, log-rank test); conversely, CD49dhigh B-CLLs (n=46) had shorter survivals, as compared to the CD49dlow subset (n=62; p=1.2x10-3). 2) Supervised analyses were performed by comparing the expression of a wide panel of surface antigens in CD49chigh vs. CD49clow and CD49dhigh vs. CD49dlow B-CLLs. In addition, B-CLL subgroups, as identified by CD49c and CD49d expression, were compared for IgVH mutations (2% cutoff), ZAP-70 expression (30% cutoff) and Rai’s stages distribution (stages 0-I vs. II-IV). According to these analyses, CD62L, CD22, CD55, CD29, CD11c, CD54 and CD40 were the molecules significantly over-expressed in good prognosis CD49chigh B-CLLs, as compared to CD49clow cases (p<0.05; t-test); consistently, CD49chigh vs. CD49clow B-CLLs had mutated:unmutated (M:UM) ratios of 2.2 vs. 0.6 (p=9.2x10-3; Chi-square Test). Bad prognosis CD49dhigh B-CLLs, as compared to CD49dlow cases, over-expressed CD38, CD29, CD49e, CD79b and displayed a lower expression of CD11c (p<0.05). In the same subsets, M:UM ratios were 0.6 (CD49dhigh) or 3.4 (CD49dlow; p=4.2x10-5; Chi-square Test); finally, the frequency of both ZAP-70+ cases and cases with advanced Rai’s stages (II-IV) was significantly higher (p=5.6x10-4 and 2.9x10-2, respectively) in CD49dhigh B-CLLs.

Conclusion: CD49c and CD49d identify B-CLL subsets with peculiar clinico-biological features, allegedly originating from different normal B cell counterparts; under a clinical standpoint, CD49c and CD49d may be employed as additional prognosticators for B-CLLs.

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