According to the Pew Research Center, a majority of X (formerly Twitter) users in the U.S. (55%) regularly consume news through the platform, exceeding the ratio for all other major social media platforms. Still, the current literature falls short in providing insights into the relative interaction patterns seen for different classes of news on this platform. To address this gap, this study provides a large-scale analysis of user interactions with different news classes, emphasizing both the bias and reliability of the publishers. To this end, we have compiled a robust dataset comprising more than 75 million tweets posted over 56 months by 2,041 labeled U.S. news publishers. Using this dataset, we study the engagement patterns across news categories, identifying several statistically significant variances. Understanding these dynamics is crucial for developing informed strategies for news dissemination, audience targeting, and content moderation. Accordingly, this study offers data-driven insights to support such strategy development.