Next-generation sequencing (NGS) has revolutionized immune profiling by allowing researchers to gain a more complete picture of B-cell and T-cell receptor repertoires. When performing translational research to discover novel immune biomarkers associated with the activation and function of tumor-infiltrating lymphocytes (TILs), the tumor microenvironment, tumor pathogenesis, and cancer treatment responses, researchers often turn to FFPE tissue obtained from biobanks or archived patient samples.  Although the DNA that encodes these receptors is more stable and easier to isolate, solely profiling DNA misses isotype information, TCR and BCR transcript expression levels, and functional TCR and BCR sequences. To gain insight into TCR and BCR isotypes, functional sequences, and actively expressed transcripts, researchers must instead work with RNA. However, RNA isolated from FFPE samples is challenging to work with due to the low quality of RNA that results from the preservation process. 

To successfully prepare immune profiling libraries from low-quality RNA isolated from FFPE tissues, the MaxiSeq kit utilizes gene-specific primers located at constant regions for reverse transcription and cDNA synthesis, followed by second-strand synthesis using gene-specific forward primers located at the FR3 regions. Two rounds of PCR amplify the CDR3 sequences from the fragmented or degraded RNA. To ensure accuracy, UMIs are incorporated during the reverse transcription step (Figure 1). The MaxiSeq workflow:

• Detects all human TCR chains (α, β, γ, δ) and BCR chains (IgA, IgD, IgE, IgG, IgM, IgK, IgL)
• Supports an input range of 200 ng–1 μg, even when starting with RNA of low RIN value

RNA extracted from FFPE tissues is highly degraded

To demonstrate the MaxiSeq kit’s ability to reliably generate accurate TCR and BCR NGS libraries from low-quality samples, two human FFPE samples were analyzed—normal lymph node (LN) and renal cell carcinoma (RCC). The RIN and DV200 values were determined to evaluate the quality of the RNA extracted from each FFPE sample (Figure 2).

FFPE sample	RIN	DV200
Lymph node	3.1	77.55%
Renal cell carcinoma	1.2	38.96%

Figure 2. Low-quality RNA from two FFPE samples was profiled using the MaxiSeq Human FFPE TCR+BCR (with UMIs). Panel A. Gel electrophoresis images of RNA isolated from FFPE lymph node (LN; middle lane) and FFPE renal cell carcinoma (RCC; right lane) tissue sections. Panel B. RIN and DV200 values indicate the low quality of the RNA.

TCR clonotypes reliably detected using degraded RNA

Profiling of the degraded RNA isolated from FFPE human lymph node tissue (Figure 3, Panel A) and FFPE renal cell carcinoma tissue (Figure 4, Panel A) resulted in the recovery of over 8,000 TCR clonotypes (Figure 3, Panel B; Figure 4, Panel B; and Table 1). Replicates from each FFPE tissue sample showed high reproducibility (Figure 3, Panel C and Figure 4, Panel C). This demonstrates the kit’s ability to unlock immune signatures even from highly degraded RNA, provided sufficient biological signal is present. The MaxiSeq kit captured TCR receptor repertoire sensitively, making it an ideal solution for TIL analysis.

BCR clonotypes reliably detected regardless of TIL content

To assess the MaxiSeq kit’s ability to detect both heavy and light BCR chains, RNA was extracted from two human FFPE samples and libraries were generated and sequenced. Over 60,000 BCR clonotypes were successfully detected in sample 2 (Figure 5, Panel A). The number of BCR clonotypes detected was lower in sample 1, which was expected due to that sample's lower lymphocyte content (Figure 5, Panel B).

To evaluate the reproducibility of results from the MaxiSeq kit across FFPE samples with varying TIL content, two replicates were analyzed from each of the two samples. Libraries from both samples showed high reproducibility, with a correlation of more than 0.96 between replicates. As expected for immune repertoire data, overlap between replicates was low (Jaccard Index of 0.38–0.47) due to high clonotype diversity (Figure 5, Panels C and D).

FFPE samples are widely used in biomarker discovery and translational research. However, much of the immune repertoire information within these samples has remained inaccessible due to the poor quality and fragmentation of RNA typically extracted from these archived tissues. While DNA-based approaches can reveal the presence of TCR and BCR gene rearrangements, only RNA sequencing provides critical insights into the expression levels and dynamic changes in TCR and BCR clonotypes across samples or over time.  

Unlocking immune repertoire data from RNA found in FFPE samples enables researchers to track clonal expansions, monitor immune responses, and discover novel immunological biomarkers—capabilities that were previously limited by technical constraints. 

The MaxiSeq assay addresses this crucial gap by providing:

• A reliable solution for profiling both TCR and BCR repertoires from highly degraded RNA
• High accuracy powered by UMIs, minimizing PCR bias and sequencing errors
• Quantitative, expression-based measurement of abundant and rare TCR/BCR clonotypes 

The MaxiSeq Human FFPE TCR+BCR (with UMIs) kit enables accurate and reproducible profiling of the full immune receptor repertoire of both TCRs and BCRs, even from highly degraded RNA found in FFPE samples, expanding the potential of retrospective studies and immuno-oncology research.

A total of 200 ng of RNA extracted from FFPE tissue of normal lymph nodes and renal cell carcinoma was used for cDNA synthesis, following the protocol found in the MaxiSeq Human FFPE TCR+BCR (with UMIs) User Manual. Gene-specific oligo-primed reverse transcription is followed by second-strand synthesis to make cDNA. Following cDNA synthesis, PCR amplification was performed using primers specific to the 5’ and 3’ universal sequences incorporated during first- and second-strand synthesis steps. A second round of PCR was performed to add library indexes. The resulting libraries were sequenced on the NextSeq 550 using a 160 bp x 10 bp x 10 bp x 136 bp run configuration. Sequencing data was analyzed using Cogent NGS Immune Profiler to characterize the immune receptor repertoire.